MemoryManager.get_all_tool_schemas() output was appended to AIAgent.tools
unconditionally — bypassing the enabled_toolsets / platform_toolsets filter.
Setting `platform_toolsets: telegram: []` had no effect: fact_store and other
memory provider tools still leaked into the tool surface on every session.
Impact on local models (per @thundercat49's benchmarks on Qwen3-30B-A3B Q4_K_M /
RTX 3090): tool-formatted prompts process at 134 tok/s vs 1,230 tok/s for plain
text. With 8 memory tool schemas injected, a simple 'hello' on Telegram took
~42s instead of ~1.7s. Small models also entered tool-call loops when memory
tools were the only tools present.
Gate condition (matches the natural meaning of enabled_toolsets):
None → no filter, inject (backward compat)
contains 'memory' → user opted in, inject
otherwise (including []) → skip injection
Co-authored-by: Teknium <127238744+teknium1@users.noreply.github.com>
Reported by @LikiusInik in Discord: on Termux only 3 built-in skills
appeared and /gh-pr-workflow + every other slash-skill from
github/productivity/mlops was missing.
Root cause: skill_matches_platform() compares sys.platform.startswith()
against the skill's platforms list. Termux is a Linux userland on
Android, but Python 3.13+ reports sys.platform == "android" instead of
"linux" — so the ~60 built-in skills tagged platforms:[linux,macos,
windows] (github-pr-workflow, google-workspace, github-auth,
huggingface-hub, etc.) all got filtered out at the listing step in
tools/skills_tool.py:_find_all_skills and never appeared as /slash
commands or in skill_view.
Fix: when is_termux() detects we're running inside Termux, accept
"linux" platform tags regardless of whether sys.platform is "linux"
(pre-3.13) or "android" (3.13+). Also accept explicit
platforms:[termux] / [android] tags. macOS-only and Windows-only
skills correctly remain excluded.
E2E (simulated TERMUX_VERSION=set + sys.platform="android"):
Before: _find_all_skills() returned ~3 skills.
After: _find_all_skills() returns 84 skills including
github-pr-workflow, google-workspace, github-auth,
huggingface-hub. Apple-only skills remain excluded.
Non-Termux Linux/macOS/Windows behavior unchanged (verified).
Tests: tests/agent/test_skill_utils.py — 9 new cases covering
android-as-Termux, the [linux,macos,windows] case, macOS-only
exclusion, explicit termux/android tags, non-Termux Android safety,
and unchanged behavior on real Linux/macOS.
* fix(skills): skip dependency dirs in skill scan
* fix(skills): widen sibling rglob scanners to use shared exclusion set
Follow-up to PR #29968. The contributor's PR widened EXCLUDED_SKILL_DIRS
in the canonical walker (iter_skill_index_files), which fixes the
user-visible discovery path. This commit sweeps the ~12 other
rglob('SKILL.md') sites that did their own ad-hoc filtering — most only
checked .git/.hub, some had no filter at all — so dependency dirs
(.venv, node_modules, site-packages, etc.) cannot leak ghost skills
through the secondary paths.
Adds agent.skill_utils.is_excluded_skill_path(path) helper. Migrates
all 13 sites to use it. Removes 3 hardcoded duplicate filter sets.
Sites touched:
agent/curator_backup.py - skill backup file count
gateway/run.py - disabled-skill response (2 sites)
hermes_cli/dump.py - skill count in env dump
hermes_cli/profile_describer.py- profile description (2 sites)
hermes_cli/profile_distribution.py - profile install count
hermes_cli/profiles.py - profile skill count
hermes_cli/skills_hub.py - category detection
tools/skill_manager_tool.py - skill name lookup (already used set, now uses helper)
tools/skill_usage.py - usage tracking + skill dir lookup (2 sites)
tools/skills_hub.py - optional skills find + scan (2 sites)
tools/skills_sync.py - bundled skills sync
E2E verified with the exact reported shape
(bring/scripts/.venv/.../typer/.agents/skills/typer/SKILL.md): no
sibling site picks up the ghost skill, all five legit-skill counts
still return 1.
* chore(infographic): retro-pop-grid bento for PR #30042 skill-scanner sweep
---------
Co-authored-by: helix4u <4317663+helix4u@users.noreply.github.com>
* feat(secrets): Bitwarden Secrets Manager integration with lazy bws install
Pull API keys from Bitwarden Secrets Manager at process startup
instead of storing them all in plaintext in ~/.hermes/.env. One
bootstrap token (BWS_ACCESS_TOKEN) replaces N per-provider keys, and
rotating a credential becomes a single change in the Bitwarden web
app.
Bitwarden defaults to source of truth: secrets pulled from BSM
overwrite any matching env vars on startup so rotations actually
take effect. Set secrets.bitwarden.override_existing: false in
config.yaml to invert.
The bws binary is auto-downloaded into ~/.hermes/bin/bws on first
use (pinned to v2.0.0, SHA-256 verified against the GitHub release
checksum file). No apt, brew, or sudo required.
New surfaces:
hermes secrets bitwarden setup — interactive wizard
hermes secrets bitwarden status — config + binary + token state
hermes secrets bitwarden sync — dry-run fetch / --apply exports
hermes secrets bitwarden disable — flip enabled: false
hermes secrets bitwarden install — just download the binary
Failures (missing binary, bad token, no network) never block Hermes
startup — they emit a one-line warning to stderr and continue with
whatever credentials .env already had.
Docs: website/docs/user-guide/secrets/{index,bitwarden}.md
Tests: tests/test_bitwarden_secrets.py (26 tests, hermetic — bws
subprocess and HTTP downloads fully mocked)
* chore(infographic): add bitwarden-secrets-manager bento-grid retro-pop-grid
Generated for PR #30035 — Bitwarden Secrets Manager integration.
Style picked via pick_pr_infographic_style.py rotation:
layout: bento-grid
style: retro-pop-grid
aspect: 1:1 square
Saved at infographic/bitwarden-secrets-manager/infographic.png
Allow custom OpenAI-compatible providers declared under `custom_providers:`
to set provider-specific `extra_body` fields and have Hermes merge them into
chat-completions requests when the matching custom endpoint is active.
This is a manual per-provider override rather than a model-name heuristic.
OpenAI-compatible Gemma thinking support is real, but the on-wire payload
shape is backend-specific: some servers want top-level `enable_thinking`,
while vLLM Gemma and NIM-style endpoints expect `chat_template_kwargs`.
A per-provider override is safer than picking one assumed payload.
Example config:
```yaml
custom_providers:
- name: gemma-local
base_url: http://localhost:8080/v1
model: google/gemma-4-31b-it
extra_body:
enable_thinking: true
reasoning_effort: high
```
For vLLM Gemma or NIM-style endpoints, use the nested shape those servers
expect:
```yaml
extra_body:
chat_template_kwargs:
enable_thinking: true
```
Changes:
- `hermes_cli/config.py`: preserve `extra_body` in normalized
`custom_providers:` entries and allow it in the validated field set.
- `hermes_cli/runtime_provider.py`: propagate custom-provider `extra_body`
as `request_overrides.extra_body` for named custom runtime resolution,
including credential-pool paths.
- `agent/agent_init.py`: at agent init, locate the matching custom-provider
entry by `base_url` (+ optional model) and merge its `extra_body` into
`AIAgent.request_overrides`, with caller-provided overrides winning on
conflicting top-level keys.
- `plugins/model-providers/custom/__init__.py`: keep existing CustomProfile
behavior (Ollama `num_ctx`, `think=False` when reasoning disabled);
user-configured `extra_body` flows through `request_overrides`.
- `website/docs/integrations/providers.md`: document the explicit
`extra_body` override and the vLLM/Gemma `chat_template_kwargs` variant.
- Tests cover config normalization, runtime propagation, model matching,
trailing-slash equivalence, fallback when no `model` field is set, and
caller-override merging precedence.
Verified end-to-end against `CustomProfile` via `ChatCompletionsTransport`:
configured `extra_body` reaches `kwargs.extra_body` on the wire request,
and coexists with profile-generated entries (Ollama `num_ctx`, `think=False`)
without clobber.
Salvaged from #29022 onto current `main`. Cosmetic typing edit in
`plugins/model-providers/custom/__init__.py` and a stale-base docs revert
in `providers.md` were dropped during cherry-pick.
Closes#29022
- Replace 18-line comment block with 3-line invariant statement
- Trim test docstrings from multi-paragraph to single-line summaries
- Trim assertion messages from 4-line to 2-line mismatch reports
- Replace 5-line WHAT comments in stubs with 1-line WHY comments
- Add ziliangdotme@gmail.com -> ziliangpeng to AUTHOR_MAP
## Summary
The background skill/memory-review fork constructed a child `AIAgent`
without propagating `enabled_toolsets` / `disabled_toolsets` from the
parent. When the parent narrowed its toolset (via `hermes tools
disable` or `config.yaml`), the fork's default `enabled_toolsets=None`
expanded to "all registered tools" — and the fork's outbound request
body sent a wider `tools[]` array than the parent's main-turn request.
Anthropic's prompt-cache key includes the `tools[]` array byte-for-byte,
so this divergence forked the cache lineage on every nudge and forced a
full prefix rewrite. On a captured ~4 hour Claude-via-Hermes session
this cost roughly 4.3 M cache-write tokens — about half of those
attributable to the per-nudge alternation between the main turn's
narrowed `tools[]` and the review fork's wider `tools[]`.
## Goal
Extend the byte-stability invariant established by PR #17276 (which
fixed `system`) to the `tools[]` slot of the request body, so the
review fork's outbound request hits the parent's warmed Anthropic
prefix cache regardless of how the parent's toolset is configured.
## Implementation
Two-line change in `agent/background_review.py`: pass
`enabled_toolsets=getattr(agent, "enabled_toolsets", None)` and the
matching `disabled_toolsets` kwarg into the `AIAgent(...)` call inside
`_spawn_background_review`. Adds an explanatory block comment that
calls out the cache-key dependency and the relationship to PR #17276.
The post-construction runtime whitelist
(`set_thread_tool_whitelist({memory, skills})`) is untouched — it
still gates which tools the model is allowed to *dispatch*. This
change aligns only what the request body *transmits*, not what the
review is allowed to do, so the safety contract from issue #15204
remains intact.
## Testing
- `tests/run_agent/test_background_review_cache_parity.py`: new
`test_review_fork_inherits_parent_toolset_config` asserts the
parent's `enabled_toolsets` and `disabled_toolsets` reach the
review-fork constructor as kwargs.
- `tests/run_agent/test_background_review_toolset_restriction.py`:
the existing `test_background_review_does_not_narrow_toolset_schema`
was inverted (its old "must NOT pass enabled_toolsets" rule was
built on the assumption that the parent always ran with the
registry default — wrong in practice when the parent is narrowed).
Renamed to `test_background_review_matches_parent_toolset_config`
and updated to assert the parent's value propagates verbatim.
- Verified the new positive test fails without the fix and passes
with it.
- Full suite for `test_background_review*`:
```
$ python -m pytest tests/run_agent/test_background_review.py \
tests/run_agent/test_background_review_summary.py \
tests/run_agent/test_background_review_toolset_restriction.py \
tests/run_agent/test_background_review_cache_parity.py -q
18 passed in 1.85s
```
## Scope
- `agent/background_review.py`: 2 added kwargs + explanatory comment.
- Two test files: one new positive test, one inverted existing test.
- No production code paths outside the review fork; no schema changes;
no public-API changes.
Refs: ziliangpeng/hermes-agent#1 (root-cause analysis with wire-level
cache-write measurements). Extends PR #17276's `system`-bytes
invariant to the `tools[]` slot.
build_write_denied_paths() resolved the protected ``.env`` via
get_hermes_home(), which is profile-aware. When a profile is active
HERMES_HOME points at ``<root>/profiles/<name>`` and ``hermes_home / ".env"``
expands to the *profile* env file only — the global ``<root>/.env`` is left
off the deny list and a write_file call against it succeeds. Since the
top-level .env supplies credentials inherited by every profile, this is a
P0 credential-exfiltration / overwrite path.
Add a parallel ``_hermes_root_path()`` helper that returns the Hermes root
(via the existing ``get_default_hermes_root()`` constant) and include
``<root>/.env`` in the deny list alongside ``<active_profile>/.env``. Both
paths now refuse write_file/patch regardless of profile state. The active
HERMES_HOME .env entry is preserved so the protection in non-profile mode
is unchanged.
A regression test exercises the profile-active scenario by pointing
HERMES_HOME at ``<tmp>/profiles/coder`` and asserting that ``<tmp>/.env``
is denied.
Fixes#15981
The contributor PR (#17936) only patched the strip path in
`_model_supports_vision()`. The auto-mode router in
`agent/image_routing._lookup_supports_vision` still only read models.dev,
so a custom-provider model declared as vision-capable would still get its
images routed through vision_analyze in the default `agent.image_input_mode:
auto` setting. Users had to set both `supports_vision: true` AND
`image_input_mode: native` to bypass the text pipeline.
Single-knob behavior now: `supports_vision: true` alone is enough in auto
mode. The strip path and the routing path consult the same resolver.
- Extract override resolution into `_supports_vision_override()` in
agent/image_routing.py and wire it into `_lookup_supports_vision()`.
- Refactor `run_agent._model_supports_vision` to call the same helper
(DRY, single source of truth for the resolution order).
- Strict YAML boolean coercion: `supports_vision: "false"` (quoted —
a common YAML mistake) no longer coerces to True via bool() truthiness.
Recognised tokens: true/false/yes/no/on/off/1/0 plus real bools and 0/1.
Unrecognised values return None and fall through to models.dev.
- Add @CNSeniorious000 to AUTHOR_MAP for release attribution.
Tests: 26 new (TestCoerceCapabilityBool, TestSupportsVisionOverride,
TestLookupSupportsVisionOverride, TestAutoModeRespectsOverride). Existing
contributor tests + image_routing + vision_native_fast_path +
native_image_buffer_isolation all green (92/92).
xAI partner integration requires Hermes to thread `encrypted_content`
reasoning items back to the Responses API on every turn so Grok can
maintain cross-turn reasoning coherence. PR #26644 (May 15) gated this
off for `is_xai_responses` on the theory that the OAuth/SuperGrok
surface rejected replayed encrypted blobs and produced the multi-turn
"Expected to have received \`response.created\` before \`error\`"
failure. That diagnosis was wrong — the prelude-SSE fallback added in
the same PR is what actually fixed that failure mode. Suppressing the
replay was an unnecessary side-effect that broke the whole point of
xAI's partnership integration.
Changes:
- agent/codex_responses_adapter.py — drop the `is_xai_responses` gate
in `_chat_messages_to_responses_input`. Keep the kwarg in the
signature for transport compatibility; update the docstring to
document the May 2026 reversal.
- agent/transports/codex.py — restore
`kwargs["include"] = ["reasoning.encrypted_content"]` on the xAI
Responses path so xAI echoes encrypted reasoning back to us.
- tests/run_agent/test_codex_xai_oauth_recovery.py — flip the three
xAI assertions (now: xAI MUST receive replayed reasoning AND we MUST
include encrypted_content in the request).
- tests/agent/transports/test_codex_transport.py — flip the
`include` assertions on `test_xai_reasoning_effort_passed` and
`test_xai_grok_4_omits_reasoning_effort`; update the allowlist
block comment.
The prelude-SSE fallback and the entitlement-403 surfacing fixes from
#26644 are untouched — they were independent fixes that happened to
ride along with the reasoning-replay gate.
Validation:
- Targeted: tests/run_agent/test_codex_xai_oauth_recovery.py +
tests/agent/transports/test_codex_transport.py → 65/65 pass
- Broader: tests/agent/transports/ + tests/run_agent/ →
1674 passed, 3 skipped, 0 failures
- E2E (real imports, isolated HERMES_HOME, ResponsesApiTransport
build_kwargs): turn-1 request carries
`include: ["reasoning.encrypted_content"]`; turn-2 input replays
the encrypted_content blob from turn-1's
`codex_reasoning_items`; native Codex unchanged.
Five call sites do os.chmod(path.parent, 0o700) without checking that
the parent resolves to a safe directory. If HERMES_HOME or another
path env var resolves to /, the chmod strips traversal permission from
the root inode and bricks the entire host.
Add secure_parent_dir() to hermes_constants.py that refuses to chmod
/ or any top-level directory (depth < 2). Replace all 5 call sites
with this helper.
Fixes#25821
PR #29182 deleted the per-session JSON snapshot writer outright because
state.db is canonical and the snapshots had no in-tree consumer. Some
users have external tooling that reads `~/.hermes/sessions/session_{sid}.json`
directly, so reintroduce the writer behind a config flag that defaults
to off.
- Add `sessions.write_json_snapshots` (default False) to DEFAULT_CONFIG
- Restore `AIAgent._save_session_log` + `_clean_session_content` as
gated methods. When the flag is off the call is a fast no-op; when
on, the writer behaves as before (atomic write, truncation guard
preserved, REASONING_SCRATCHPAD → think tag normalization)
- Re-derive the target path from `agent.session_id` on each call so
`/branch` and `/compress` re-points happen automatically — no need
to restore the explicit re-point bookkeeping at call sites
- Wire the single call site in `_persist_session` (the cleanup-on-exit
hook). Did NOT restore the 7 intra-turn calls the original PR deleted
— those were redundant writes within the same turn that doubled disk
I/O without adding any persistence guarantee `_persist_session` does
not already provide
- Read the flag once at agent init via `load_config()`, cache as
`agent._session_json_enabled`
- Update `TestNoSessionJsonSnapshot` → `TestSessionJsonSnapshotOptIn`
to pin behavior: default off (no file), opt-in true (file written),
no-op method on default agents, logs_dir retained unconditionally
- Update CONTRIBUTING.md and the bundled `hermes-agent` skill to
document the flag and its default
state.db now stores every message field the JSON snapshot stored. Removed
the method, all 7 call-sites, and ~13 test stubs that suppressed its file I/O.
Body is in git history if it ever needs to come back.
The 'tool_name' key on role=tool messages is an internal Hermes field
(stored in the messages.tool_name SQLite column for FTS indexing) that
is not part of the OpenAI Chat Completions schema. Strict OpenAI-compatible
providers — notably Moonshot AI (Kimi) — reject it with HTTP 400:
Error from provider: Extra inputs are not permitted,
field: 'messages[N].tool_name', value: 'execute_code'
Add 'tool_name' to the sanitize block in ChatCompletionsTransport.convert_messages
alongside the existing Codex Responses API fields (codex_reasoning_items,
codex_message_items) so it is popped before the request is sent.
Reproducer:
hermes chat --model kimi-k2.6
> list the top 5 Hacker News stories
-> assistant emits tool_call(execute_code)
-> tool result message gets tool_name='execute_code'
-> next turn's payload includes messages[N].tool_name -> 400
Permissive backends (MiniMax, OpenRouter on most routes) ignore the extra
field and were masking the bug.
`AIAgent.__init__` was eagerly calling
`_check_compression_model_feasibility()` which probes the auxiliary
provider chain and runs `get_model_context_length()` (potentially
network-bound) to decide whether the configured auxiliary model can
fit a full compression-threshold window. That cost ~440ms cold on
every agent construction.
Most `chat -q` invocations finish in 1-5 seconds and never accumulate
enough context to trip the compression threshold, so the feasibility
check is pure overhead. The result is also only consumed when
compression actually fires (the function adjusts the live threshold
downward if the aux model can't fit; absent that mutation, the gate
in `conversation_loop.py:442` would never fire anyway).
Defer to first `compress_context()` call via
`agent._compression_feasibility_checked` sentinel. Runs at most once
per agent lifetime, just before the first compression pass. The
warning storage (`_compression_warning`) and gateway replay
machinery is unchanged — it still emits to status_callback on the
first turn that actually needs compression.
E2E timing (chat -q 'hi', 3 runs each):
BEFORE AFTER delta
median wall 2.03s 1.86s -8% (-169ms)
min wall 1.92s 1.63s -15% (-293ms)
Real cold-start observation (synthetic 31-turn agent loop): identical
behavior since feasibility check fires once on first compression and
caches. No semantic difference for sessions that DO compress.
UX trade-off: users with broken auxiliary-provider config no longer
see the warning at session start. They see it when compression first
fires — which is exactly when it matters. For users with working
config (the vast majority), the warning never fires anyway, so the
deferral is invisible.
Tests:
- tests/run_agent/test_compression_feasibility.py — 16/16 pass
(the one test that asserted call-at-init was updated to drive the
lazy check explicitly via agent._check_compression_model_feasibility())
- Live tmux session: 2-turn conversation + tool call completes clean,
zero errors in agent.log
XAI_BASE_URL / HERMES_XAI_BASE_URL let users repoint the OAuth-authenticated
inference endpoint, but the env override was an unguarded credential-leak
vector: a tampered .env or hostile shell init setting
XAI_BASE_URL=https://attacker.example/v1 would silently ship the SuperGrok
OAuth bearer to a third party on every request.
Add _xai_validate_inference_base_url() that pins the host to x.ai or a
*.x.ai subdomain and rejects non-HTTPS. On rejection, fall back to the
default with a warning rather than raise — a bad env var should not
deadlock auth, but should never leak the bearer either.
Apply at all three sites that read the env override for xai-oauth:
- hermes_cli/auth.py resolve_xai_oauth_runtime_credentials (main path)
- hermes_cli/auth.py _xai_oauth_loopback_login (initial login)
- agent/auxiliary_client.py _resolve_xai_oauth_for_aux (aux client)
E2E validated against four scenarios: attacker.example, lookalike
api.x.ai.evil.com, http:// downgrade on api.x.ai, and legit custom.x.ai
subdomain (which still resolves correctly).
Discovered while comparing against the opencode-grok-auth plugin
(github.com/ysnock404/opencode-grok-auth), which highlighted the same
guard on the OpenCode side.
* perf(config): add load_config_readonly() fast path for hot agent loop
`load_config()` is called from the agent loop's per-API-call hot path via
`get_provider_request_timeout()` and `get_provider_stale_timeout()` —
both invoked once per turn from `_resolved_api_call_timeout()` in
run_agent.py.
Profiling a synthetic 20-tool-call agent run revealed:
- 21 invocations of `load_config()` cumulating 56ms (~17% of agent loop)
- 34,398 deepcopy calls totaling 37ms (config defensive deepcopy + chain)
- 8,652 `_expand_env_vars` invocations (~412 per turn)
Microbench (cache-hit, real config.yaml present):
load_config() 265us/call (125us deepcopy + 140us infra)
load_config_readonly() 138us/call (~48% faster)
`load_config_readonly()` returns the cached dict directly without the
defensive deepcopy. Documented contract: caller must not mutate. Returns
plain dict (not MappingProxyType) so downstream `isinstance(x, dict)`
guards keep working — caught during initial implementation when
MappingProxyType broke get_provider_request_timeout's guard logic.
Wired into hermes_cli/timeouts.py (the two functions called per agent
turn). load_config() is unchanged for the 263 other call sites that
mutate the result before save_config(), are not in the hot path, or
where the safety guarantee matters more than the perf.
Profile A/B (cached config, 21-turn agent loop):
BEFORE AFTER delta
get_provider_request_timeout 55ms 16ms -71%
total function calls 399k 160k -60%
deepcopy calls (in hotspots) 34,398 ~0 ~elim
Verified:
- isinstance(load_config_readonly(), dict) is True
- timeout/stale resolutions correct
- load_config() still returns isolated mutable deepcopies
- tests/hermes_cli/test_config*.py / test_timeouts.py: 102/102 pass
- tests/cli/ + tests/agent/test_auxiliary_client.py: 883/883 pass
* perf(redact): substring pre-screens skip non-matching regex chains
Every log record passes through `RedactingFormatter.format` which calls
`redact_sensitive_text`, which historically ran ALL 13 secret-pattern
regexes against every line — including DB connection strings, JWTs,
Discord mentions, Signal phone numbers, etc. — even for typical clean
log records like 'INFO run_agent: API call completed'.
Add cheap substring pre-checks before each regex pass. False positives
still run the regex (which then matches nothing); false negatives are
impossible because every pattern requires the gated substring to match
its leading anchor:
- `_PREFIX_RE` gated on any of 33 known credential prefix substrings
- `_ENV_ASSIGN_RE` gated on `=` in text
- `_JSON_FIELD_RE` gated on `:` and `"` in text
- `_AUTH_HEADER_RE` gated on `uthorization`/`UTHORIZATION` in text
- `_TELEGRAM_RE` gated on `:` in text
- `_PRIVATE_KEY_RE` gated on `BEGIN` and `-----`
- `_DB_CONNSTR_RE` gated on `://` in text
- `_JWT_RE` gated on `eyJ` in text
- URL userinfo/query gated on `://`
- `_redact_form_body` gated on `&` and `=`
- `_DISCORD_MENTION_RE` gated on `<@`
- `_SIGNAL_PHONE_RE` gated on `+`
Microbench (5 typical log records, 20k iterations each):
BEFORE AFTER delta
redact_sensitive_text per call 5.63us 1.79us -68%
Real-world impact: ~244 log records emitted in a 30-turn agent loop, so
the chain saves ~1ms of CPU per conversation. Bigger win is the
reduction in regex execution and GC pressure during heavy logging
sessions (verbose logging, gateway message processing).
Security regression test: 30 secret-containing inputs (sk-/ghp_/JWT/DB
connstr/Auth-Bearer/private key/URL userinfo/Discord/Signal/etc.)
verified to produce identical redacted output before/after. All 75
existing tests/agent/test_redact.py cases pass.
The `?access_token=foo&code=bar` (bare query string, no scheme) case
that 'leaks' is pre-existing behavior — the URL query redaction
requires a well-formed URL with scheme+host. Not a regression.
* perf(run_agent): cache _needs_thinking_reasoning_pad result per (provider, model, base_url)
Profile of a 31-turn synthetic agent run shows `_needs_thinking_reasoning_pad`
fires 495 times (~16 per turn) and each call ran 3 helper methods, each
hitting `base_url_host_matches` 1-4 times via `urlparse`. Total cost:
3,342 base_url_host_matches calls + 3,373 urlparse calls accounting for
~36ms of agent-loop overhead (~7% of the entire post-network work).
Provider / model / base_url don't change during a conversation except via
`switch_model` and fallback activation — both of which already overwrite
those attributes atomically. Cache the result on a tuple key; since the
key is derived from the very fields that would change, the cache
auto-invalidates on the next read after a switch. No manual invalidation
needed in switch_model / _try_activate_fallback.
Profile A/B (31-turn cached-config agent run):
BEFORE AFTER delta
_needs_thinking_reasoning_pad cum 18ms 1ms -94%
_copy_reasoning_content_for_api cum 17ms 1ms -94%
base_url_host_matches calls 3,342 372 -89%
urlparse calls 3,373 403 -88%
total function calls 296k 223k -25%
Verified:
- tests/run_agent/test_deepseek_reasoning_content_echo.py: 36/36 pass
- tests/run_agent/ (full): 1383/1383 pass + 3 skipped
Introduces make_tool_result_message() in tool_dispatch_helpers.py as the
single place where tool-result message dicts are built. All six construction
sites in tool_executor.py, agent_runtime_helpers.py, and mini_swe_runner.py
now use it, so tool_name is set in memory from the moment a message is
created rather than relying on fallback logic in the flush paths.
Fixes blank tool_name in both state.db and JSON session logs.
Adds tests.
Follow-up to #28452. detect_stale_running() was calling
_record_task_failure() on every reclaim, which ticked the
consecutive_failures counter. With the default failure_limit=2,
two legitimately long-running tasks (>4 h without explicit
heartbeat) would auto-block via the spawn-failure circuit
breaker — even though no worker actually failed.
Stale reclaim is dispatcher-side absence-of-heartbeat detection,
not a worker fault. Removed the _record_task_failure() call;
the 'stale' event in task_events is still the audit surface,
but the failure counter is now reserved for spawn_failed /
timed_out / crashed (real failures).
Also documents the heartbeat requirement:
- KANBAN_GUIDANCE in agent/prompt_builder.py now states the
rule ('call kanban_heartbeat at least once an hour for tasks
running longer than 1 hour') so workers learn the contract.
- kanban.md adds the stale event row to the events table and
flags the heartbeat requirement in the worker lifecycle list.
New regression test: test_detect_stale_does_not_tick_failure_counter
locks in the new behaviour.
1. trajectory_compressor.py: yaml.safe_load() returns None on empty
files, crashing with TypeError on `if 'tokenizer' in data`. Fix by
adding `or {}` fallback. (HIGH — blocks startup with empty config)
2. 6 files with fcntl.flock(LOCK_UN) in finally blocks without
try/except: cron/scheduler.py, hermes_cli/auth.py,
agent/shell_hooks.py, tools/skill_usage.py,
tools/environments/file_sync.py, tools/memory_tool.py. If unlock
raises OSError, fd.close() is skipped and the lock is held forever.
The msvcrt branches already had try/except; the fcntl branches did
not. Fix by wrapping in try/except (OSError, IOError): pass.
3. agent/copilot_acp_client.py line 639: TOCTOU race — path.exists()
followed by path.read_text() with no try/except. If file is deleted
between the check and the read, FileNotFoundError propagates. Fix
by using try/except FileNotFoundError.
4. gateway/sticker_cache.py: non-atomic write via Path.write_text()
can leave truncated JSON on crash, causing JSONDecodeError on next
load. Fix by writing to tempfile + fsync + os.replace (atomic).
Skill bundles are tiny YAML files in ~/.hermes/skill-bundles/ that
group several skills under one slash command. Invoking /<bundle-name>
from any surface (CLI, TUI, dashboard, any gateway platform) loads
every referenced skill into a single combined user message.
Use cases:
- /backend-dev → loads github-code-review + test-driven-development
+ github-pr-workflow as one bundle.
- /research → loads several research skills together.
- Team task profiles shared via dotfiles.
Behavior:
- Bundles take precedence over individual skills when slugs collide.
- Missing skills are skipped with a note, not fatal.
- No system-prompt mutation — bundles generate a fresh user message
at invocation time, the same way /<skill> does. Prompt cache stays
intact.
- Works in CLI dispatch, gateway dispatch, autocomplete (CLI + TUI),
/help display.
Schema (~/.hermes/skill-bundles/<slug>.yaml):
name: backend-dev
description: Backend feature work.
skills:
- github-code-review
- test-driven-development
instruction: |
Optional extra guidance prepended to the loaded skills.
New module: agent/skill_bundles.py — load, scan, resolve, build
invocation message, save, delete. yaml.safe_load only; broken
bundles log a warning and are skipped, never raise.
New CLI subcommand: hermes bundles {list,show,create,delete,reload}.
Implementation in hermes_cli/bundles.py; wired in hermes_cli/main.py.
'bundles' added to _BUILTIN_SUBCOMMANDS so plugin discovery skips it.
New in-session slash command: /bundles lists installed bundles in
both CLI and gateway. /<bundle-name> dispatch added to CLI (cli.py)
and gateway (gateway/run.py) before the existing /<skill-name> path.
Autocomplete: SlashCommandCompleter gained an optional
skill_bundles_provider parameter that defaults to None — the prompt
shows '▣ <description> (N skills)' for bundles vs '⚡' for skills.
Tests:
- tests/agent/test_skill_bundles.py — 33 tests covering slugify,
scan/cache freshness, resolve (including underscore→hyphen
Telegram alias), build_bundle_invocation_message (loading, missing
skills, user/bundle instruction injection, dedup), save/delete,
reload diff, list sort.
- tests/hermes_cli/test_bundles.py — 8 tests for the CLI
subcommand (create/list/show/delete/reload, --force, missing
bundle errors).
- tests/gateway/test_bundles_command.py — 4 tests for the gateway
handler and bundle resolution priority.
Live E2E: verified subprocess invocations of hermes bundles
{list,create,show,reload,delete} round-trip correctly against an
isolated HERMES_HOME.
Docs:
- website/docs/user-guide/features/skills.md — new 'Skill Bundles'
section with quick example, YAML schema, management commands,
behavior notes.
- website/docs/reference/cli-commands.md — 'hermes bundles' added to
the top-level command table and given its own subcommand section.
Salvages #24402 by @RyanRana. The KANBAN_GUIDANCE block (~835 tokens)
is session-static — the dispatcher decides at spawn time whether the
process is a kanban worker via the kanban_show tool's check_fn (gated
on HERMES_KANBAN_TASK env var). Re-checking 'kanban_show' in
valid_tool_names and re-loading the reference on every system-prompt
rebuild (init + each context compression) is wasted work.
Caches the resolved string on agent._kanban_worker_guidance once in
agent_init and consumes it in system_prompt.build_system_prompt(),
with a getattr fallback for code paths that bypass agent_init.
The existing ``_is_entitlement_failure`` heuristic only fires when
the response body contains specific substrings ("do not have an
active Grok subscription", etc.). xAI has been seen to 403 standard
SuperGrok subscribers with a terser body that doesn't match those
keywords (#26847), and the recovery path would then mint a fresh
token, get a fresh 403, and loop until Ctrl+C.
Add a defense-in-depth check at the recovery call site: any 403 on
``provider == "xai-oauth"`` short-circuits ``try_refresh_current``
so the error surfaces immediately with the friendly hint from
``_summarize_api_error``. Keeps the existing keyword path for all
other providers untouched.
Qwen3.x and DeepSeek-V3.x default to chatty/hallucinatory tool use without
enforcement steering — agents narrate "calling tool X" without actually
emitting a tool call, or run partial loops. Both model families fit the
same failure pattern TOOL_USE_ENFORCEMENT_GUIDANCE was already injected
for (gpt, codex, gemini, gemma, grok, glm).
Co-authored-by: briandevans <252620095+briandevans@users.noreply.github.com>
Squashed salvage of:
- 403e567ce fix(agent): add qwen and deepseek to TOOL_USE_ENFORCEMENT_MODELS
- 9433eabe7 test(agent): use realistic qwen-plus identifier in enforcement test
Fixes#28079.
The conversation_loop.py references _pool_may_recover_from_rate_limit which
was defined in run_agent.py. After the conversation-loop extraction refactor,
the helper was no longer in the same module scope. Wrap the call as
_ra()._pool_may_recover_from_rate_limit() to route through the run_agent
monkeypatch namespace where the helper is available.
Adds regression test in test_gemini_fast_fallback.py.
Fixes: MAILROOM Email Triage NameError, OPS Execution Monitor NameError.
The background review prompts (_SKILL_REVIEW_PROMPT and
_COMBINED_REVIEW_PROMPT) now include explicit protection rules
for bundled, hub-installed, and pinned skills — aligning with
the curator's existing policy at curator.py L345/350.
Before this change, bg-review could freely rewrite bundled skills
like 'hermes-agent' or pinned skills, while the 7-day curator
explicitly skips them.
The review agent now sees:
• Bundled skills (shipped with Hermes)
• Hub-installed skills (installed via hermes skills install)
• Pinned skills (marked via hermes curator pin)
If only protected skills need updating, the review says
'Nothing to save.' and stops.
Fixes#27644
xAI's /v1/responses and /v1/chat/completions endpoints reject tool schemas
whose enum values contain a forward slash with a generic HTTP 400 'Invalid
arguments passed to the model.' before any token is emitted — the schema
compiler trips on the '/' character regardless of where it appears.
Most commonly hit by MCP-derived tools whose enum lists HuggingFace model
IDs ('Qwen/Qwen3.5-0.8B', 'openai/gpt-oss-20b') or owner/name environment
identifiers.
Mirrors the existing strip_pattern_and_format sanitizer (PR for #27197).
The new strip_slash_enum walks tool parameters and drops the entire enum
keyword when any value contains '/' — keeping it partial would still 400
since xAI's failure is all-or-nothing on the enum. The field description
still reaches the model so the prompting hint is preserved.
Wired in at both code paths for parity:
- agent/chat_completion_helpers.py (main agent xAI Responses path)
- agent/auxiliary_client.py (aux client xAI Responses path, matching
the same parity guarantee 2fae8fba9 established for pattern/format)
Salvaged from #28021 by @Slimydog21 — contributor's branch was severely
stale (would have reverted ~5000 LOC across azure/kanban/i18n); fix
re-applied surgically on current main with their sanitizer + 9 tests
preserved verbatim. Author noreply email used (original was a Mac
hostname leak).
When a Codex OAuth refresh token is permanently invalidated (HTTP 400/401/403,
token revoked or reused), _mark_exhausted was called but auth.json was left with
the dead credentials. On the next session, _seed_from_singletons re-read
auth.json and re-seeded the pool with the same revoked token, triggering the
same terminal failure in a loop.
Add _is_terminal_codex_oauth_refresh_error to auth.py and a matching quarantine
block in _refresh_entry: when a terminal error is detected and auth.json holds
no newer tokens, clear access_token/refresh_token from auth.json and remove all
device_code-sourced pool entries from memory. Mirrors the Nous quarantine added
in c90556262 and the xAI quarantine in #28116.
Also add a pre-refresh sync from auth.json before calling refresh_codex_oauth_pure,
matching the xAI and Nous patterns, to avoid refresh_token_reused races when
multiple Hermes processes share the same auth.json singleton.
Salvaged from #27911 by @EloquentBrush0x — contributor's branch was severely
stale (would have reverted ~5000 LOC across azure/kanban/i18n subsystems);
fix re-applied surgically on current main with their predicate and tests preserved.
PR #28102 made the summary-failure abort path the unconditional default,
changing established behavior. Gate it behind config.yaml flag
`compression.abort_on_summary_failure` (default False = historical
fallback-placeholder behavior).
- hermes_cli/config.py: new `compression.abort_on_summary_failure` key,
default False, documented inline.
- agent/agent_init.py: read the flag from compression config and pass to
ContextCompressor.
- agent/context_compressor.py: `__init__` accepts `abort_on_summary_failure`
(default False). `compress()` failure branch gates the abort on the
flag; when False, falls through to the restored legacy fallback path
(static "summary unavailable" placeholder + drop middle window).
- tests: restore original fallback expectations as default; add new
TestAbortOnSummaryFailure class for the opt-in mode.
Gateway/CLI plumbing (force=True on /compress, hygiene/handler abort
detection, locale `gateway.compress.aborted` key) from PR #28102 stays
intact — those paths only fire when `_last_compress_aborted` is True,
which now only happens when the flag is enabled.
When refresh_xai_oauth_pure raises a terminal error (HTTP 400/401/403,
i.e. revoked or reused refresh token), _refresh_entry's existing race-
recovery path re-syncs from auth.json and returns if another process has
already rotated the tokens. If auth.json still holds the same stale
token pair, the function fell through to _mark_exhausted — leaving the
dead credentials in auth.json. On the next Hermes startup _seed_from_singletons
re-seeded the pool from those stale tokens, causing the same failure loop
on every session.
Fix: after the auth.json re-sync check in the xAI-oauth error handler,
detect terminal errors with the new _is_terminal_xai_oauth_refresh_error
helper and apply a quarantine:
- Clear access_token and refresh_token from providers["xai-oauth"]["tokens"]
in auth.json so they are not re-seeded.
- Write a last_auth_error entry for hermes doctor / auth status diagnostics.
- Remove all loopback_pkce entries from the in-memory pool so the current
session stops retrying with the dead credentials.
Mirrors the identical quarantine already in place for Nous OAuth
(c90556262).
Closes the parity gap introduced when c90556262 added Nous-only terminal
error handling without a corresponding xAI-oauth path.
When xAI returns a subscription/entitlement error through an SSE
``type=error`` frame, ``_StreamErrorEvent`` is raised with
``status_code=None``. This caused ``_classify_by_status`` (step 2 of
``classify_api_error``) to be skipped entirely, and the Grok-specific
phrases ("do not have an active Grok subscription", "out of available
resources") appeared in none of the message-pattern lists. The error
fell through to ``FailoverReason.unknown (retryable=True)``, burning
``max_retries`` on every affected X Premium+ / SuperGrok user before
the agent stopped — and ``_is_entitlement_failure`` was never called
because it only fires under ``FailoverReason.auth``.
The HTTP 403 path already handled this correctly (``_classify_by_status``
returns ``auth/non-retryable`` for 403). Add an explicit pattern block
at step 1 (highest priority, before the ``status_code`` guard) so both
code paths route to ``FailoverReason.auth, retryable=False,
should_fallback=True`` — matching the 403 path exactly.
Add three regression tests in ``Fix D`` section of
``test_codex_xai_oauth_recovery.py``:
- primary "do not have an active Grok subscription" phrase
- "out of available resources" + "grok" variant
- unrelated ``_StreamErrorEvent`` must not be reclassified
xAI is a first-class provider in hermes-agent with its own credential
pool entry (XAI_API_KEY / xai-oauth). API keys follow the format
xai-<60+ alphanumeric chars> and were absent from _PREFIX_PATTERNS in
agent/redact.py.
When a key appears raw in log output, tool results, or error messages,
it passed through completely unmasked. The ENV-assignment and Bearer
header patterns catch the most common cases, but a raw token in a
stack trace or debug print had no protection.
Verified before fix:
redact_sensitive_text("using key xai-ABCD...rstu to call xAI", force=True)
# "using key xai-ABCD...rstu to call xAI" <- exposed
After fix:
# "using key xai-AB...rstu to call xAI" <- masked
Five unit tests added to TestXaiToken covering bare token masking,
env assignment, short-prefix false positive, company name false
positive, and visible prefix in masked output.
When auxiliary compression's summary generation returns None (aux model
errored, returned non-JSON, timed out, etc.) the compressor previously
still dropped every middle message between compress_start..compress_end
and replaced them with a static 'Summary generation was unavailable'
placeholder. The session kept going but the user silently lost N turns
of context for nothing.
New behavior: on summary failure, compress() aborts entirely — returns
the input messages unchanged and sets _last_compress_aborted=True. The
existing _summary_failure_cooldown_until gate (30-60s) keeps the aux
model from being burned on every turn. Auto-compress callers detect
the no-op (len(after) == len(before)) and stop looping. The chat is
'frozen' at its current size until the next /compress or /new.
Manual /compress (CLI + gateway) now passes force=True which clears
the cooldown so users can retry immediately after an auto-abort. If
the manual retry also fails, the user gets a visible warning telling
them nothing was dropped and how to retry.
- agent/context_compressor.py: compress() gains force= kwarg; failure
branch sets _last_compress_aborted and returns messages unchanged
instead of inserting placeholder.
- run_agent.py: _compress_context() detects abort, surfaces warning,
skips session-rotation entirely, returns messages unchanged.
- cli.py + gateway/run.py: manual /compress paths pass force=True.
- gateway/run.py: hygiene + /compress handlers detect _last_compress_aborted
and emit the new 'Compression aborted' warning (gateway.compress.aborted)
instead of the old 'N historical messages were removed' message.
- locales/*.yaml: new gateway.compress.aborted key in all 16 locales.
- tests: updated to assert the abort contract (messages preserved,
compression_count not incremented, abort flag set, no placeholder
leaked). New test_force_true_bypasses_failure_cooldown covers the
manual-retry path.
xAI's /responses endpoint rejects tool schemas that contain pattern or
format JSON Schema keywords with HTTP 400. chat_completion_helpers.py
already strips these for the main-agent xAI/xai-oauth path (lines
294-302), but _CodexCompletionsAdapter.create() — used for every xAI
OAuth auxiliary call (kanban decomposer, profile describer, etc.) —
passed raw tool schemas without sanitization.
MCP tools that carry pattern/format keywords (common for string fields)
silently caused every auxiliary call over xAI OAuth to fail with an
HTTP 400, while the main agent worked fine. Parity fix: call
strip_pattern_and_format() on the tool list before converting to
Responses API format, matching the main-agent guarantee.
Cherry-pick of @sharziki's #27022 routed Azure Foundry through
_requires_bearer_auth, which also triggered the MiniMax-specific
beta-strip in _common_betas_for_base_url — dropping the 1M-context
beta from Azure even though Azure needs it for 1M context.
Split the strip predicate: introduce _is_minimax_anthropic_endpoint
so the fine-grained-tool-streaming and context-1m strips only fire
for MiniMax hosts, leaving Azure's bearer-auth header swap intact
without losing 1M context.
Also add a regression test that asserts Azure gets Bearer auth,
the api-version query param, and the context-1m-2025-08-07 beta.
Azure AI Foundry's Anthropic-style endpoint requires
`Authorization: Bearer` instead of `x-api-key`. Add `azure.com` to
`_requires_bearer_auth()` so the existing Bearer path at line 586 fires
before the generic third-party branch sets `api_key` (x-api-key).
Fixes#26970
* feat(session_search): single-shape tool with discovery, scroll, browse — no LLM
Replaces the LLM-summarized session_search with a single-shape tool that
returns actual messages from the DB. Three calling shapes inferred from
args (no mode parameter):
1. Discovery — pass query. FTS5 + anchored ±5 window + bookends per hit,
all in one call. ~20ms on a real DB instead of ~90s for the previous
three aux-LLM calls.
2. Scroll — pass session_id + around_message_id. Returns a window
centered on the anchor. To paginate, re-anchor on the first/last id
of the returned window. Boundary message appears in both windows
as the orientation marker. ~1ms per scroll call.
3. Browse — no args. Recent sessions chronologically.
Bookend_start (first 3 user+assistant msgs) and bookend_end (last 3) give
the agent goal + resolution on every discovery hit, so a single tool call
reconstructs a long session's arc without loading the whole transcript.
The aux-LLM summary path is gone: it cost ~$0.30/call, took ~30s, and
laundered FTS5 hits through a model that could confabulate when the right
session wasn't in the hit list. The merged shape returns byte-for-byte
content from SQLite.
History:
- PR #20238 (JabberELF) seeded the fast/summary dual-mode split.
- PR #26419 (yoniebans) expanded to fast/guided/summary with bookends,
multi-anchor drill-down, default-mode config, and a teaching skill.
This PR collapses that toolkit into one shape with explicit scroll
support, drops the summary path, drops the mode parameter, drops the
config knob, drops the skill. JabberELF's seed work is acknowledged via
the AUTHOR_MAP entry.
Validation:
- 38/38 tool tests pass (tests/tools/test_session_search.py)
- 12/12 get_messages_around tests pass (tests/hermes_state/)
- 11/11 get_anchored_view tests pass (tests/hermes_state/)
- Full tests/tools/ run: 5168 passing, 2 failures pre-exist on main
(test ordering in test_delegate.py, unrelated)
- E2E against live state DB: discovery 20ms, scroll 1ms, browse 280ms;
pagination forward+backward works with boundary-message orientation;
error paths return clean tool_error responses
Co-authored-by: JabberELF <abcdjmm970703@gmail.com>
Co-authored-by: yoniebans <jonny@nousresearch.com>
* chore(session_search): prune dead LLM-summary config and docs
Companion to the single-shape rewrite. The auxiliary.session_search config
block, max_concurrency / extra_body tunables, and matching docs sections
all referenced the removed LLM summarization path. Removing them so users
don't try to tune knobs that nothing reads.
- hermes_cli/config.py: drop dead auxiliary.session_search block from
DEFAULT_CONFIG. Leftover keys in user config.yaml are harmless and
ignored.
- hermes_cli/tips.py: drop two tips referencing the removed
max_concurrency / extra_body knobs.
- website/docs/user-guide/configuration.md: drop 'Session Search Tuning'
section and the auxiliary.session_search block from the example.
- website/docs/user-guide/features/fallback-providers.md: drop session_search
rows from the auxiliary-tasks tables and the dedicated tuning subsection.
- website/docs/reference/tools-reference.md: rewrite the session_search
entry to describe the new three-shape behaviour.
- CONTRIBUTING.md: update the file-tree description.
- tests/tools/test_llm_content_none_guard.py: remove TestSessionSearchContentNone
class and test_session_search_tool_guarded — both guard against an
unguarded .content.strip() call site in _summarize_session() that no
longer exists.
Validation: 97/97 targeted tests still pass (hermes_state + session_search +
llm_content_none_guard). Config tests 55/55.
---------
Co-authored-by: JabberELF <abcdjmm970703@gmail.com>
Co-authored-by: yoniebans <jonny@nousresearch.com>
The system prompt's 'Conversation started:' line carried minute precision
(%I:%M %p), making it byte-unstable across every rebuild path. Within a
CLI session the in-memory cache held, but on the gateway path (fresh
AIAgent per turn → restore from session DB), any silent failure in the
read or write path dropped the cache stem and forced a full re-prefill
on every subsequent turn. Local prefix-caching backends (llama.cpp /
vLLM) saw this as KV-cache invalidation; remote prefix-caching providers
saw it as an Anthropic-style cache miss.
Three changes:
1. Date-only timestamp ('Sunday, May 17, 2026' instead of '... 03:42 PM').
System prompt now byte-stable for the full day. The model can still
query exact time via tools when it actually needs it. Credit:
@iamfoz (PR #20451).
2. Loud logging on session DB write failures. The update_system_prompt
call used to log at DEBUG, hiding disk-full / locked-database / schema
drift behind a silent fall-through that forced fresh rebuilds on
every subsequent turn. Now WARN with the session id and exception so
persistent issues show up in agent.log without verbose mode.
3. Three-way stored-state distinction on read. The previous
'session_row.get("system_prompt") or None' collapsed three states
into one (missing row / null column / empty string). Now we tell them
apart and WARN when a continuing session lands on null/empty (which
means the previous turn's write never persisted — every subsequent
turn rebuilds and the prefix cache misses every time).
The restore block is extracted into _restore_or_build_system_prompt()
so the prefix-cache path can be unit-tested in isolation.
E2E proof: fresh AIAgent constructed for turn 2 across a minute-boundary
sleep restores byte-identical bytes from the session DB. NULL stored
prompt fires the new warning. Date-only timestamp survives the rebuild
path. All on real SessionDB, no mocks.
Tests:
- tests/agent/test_system_prompt_restore.py (10 new tests)
- tests/run_agent/test_run_agent.py::TestBuildSystemPrompt::
test_datetime_is_date_only_not_minute_precision
Closes#20451 (date-only), #18547 (prefix stabilization),
#8689 (stabilize timestamp across compression), #15866 (timestamp
caching question), #8687 (compression timestamp), #27339
(claim #3: live timestamp in cached system prompt).
Co-authored-by: Martyn Forryan <9133432+iamfoz@users.noreply.github.com>
Grok models hit the same failure modes that OPENAI_MODEL_EXECUTION_GUIDANCE
addresses for GPT/Codex: claiming completion without tool calls
('to be honest, I didn't create the file yet'), suggesting workarounds
instead of using existing tools (proposing a folder-based memory system
when the memory tool exists), replying with plans instead of executing.
TOOL_USE_ENFORCEMENT_GUIDANCE was already injected for any model whose
name contains 'grok' (TOOL_USE_ENFORCEMENT_MODELS). This extends the
follow-on family-specific block — OPENAI_MODEL_EXECUTION_GUIDANCE
(tool_persistence / mandatory_tool_use / act_dont_ask / prerequisite_checks
/ verification / missing_context) — to grok-named models too.
The OPENAI_ prefix is retained for backwards compat with imports/tests;
docstring + inline comment now note that the body is family-agnostic and
the prefix reflects origin, not exclusivity.
Tests cover the OpenRouter slug (x-ai/grok-4.3) and the xai-oauth bare
name (grok-4.3), plus a negative control on claude.
E2E verified against a real AIAgent build of the system prompt for both
xai-oauth and openrouter grok models.
