Four independent pre-request stalls sat on the critical path between
prompt submission and the first streamed token, measured with cProfile
against a live process:
1. Discord capability detection (~2.0s, worst 5s): get_tool_definitions
-> _get_dynamic_schema made a BLOCKING https call to discord.com
inside AIAgent.__init__ for any user with DISCORD_BOT_TOKEN set, on
every platform, every cold process. Now non-blocking: memory cache ->
24h disk cache -> permissive default + one background detection that
seeds the disk cache for the next process. The permissive default is
pinned per-process so tool schemas never flip mid-conversation
(prompt-cache safety); it mirrors the existing detection-failure
fallback (all actions exposed, 403s enriched at call time).
2. Ollama /api/show probe (~0.3s): get_model_context_length step 5e
POSTed to <base_url>/api/show for KNOWN providers (openrouter etc.),
got a 404, and never cached the miss - so every fresh process paid a
full HTTP round-trip. Known non-Ollama providers now skip the probe;
local/custom/unknown endpoints keep the exact previous behavior.
3. env_probe subprocess sweep (~0.5s): the Python-toolchain probe ran
4-8 subprocess calls inside the FIRST system prompt build. Now warmed
off-thread during agent init; the prompt build hits the cache (same
lock, so a mid-flight warm just joins instead of recomputing).
4. tools.mcp_tool import (~0.4s): the between-turns MCP refresh in
build_turn_context imported the whole mcp package even with zero MCP
servers configured. MCP tools can only exist if tools.mcp_tool was
already imported (discovery/reload paths), so gate the import on
sys.modules membership - no behavior change for MCP users.
CLI additionally pre-imports run_agent + openai off-thread during the
idle banner window (same pattern as the /model picker prewarm), hiding
the remaining ~1.5s of module imports while the user types. Fixes 1-4
apply to every interaction layer (CLI, gateway, TUI, desktop, cron).
Measured cold first turn (submit -> request dispatched, openrouter,
discord token set): 4.3s before -> 0.9s after CLI prewarm (~80%); the
agent-side non-import cost drops 2.9s -> 0.36s (init) + 0.27s (turn
prologue).
_capability_cache was a single module-level dict shared across all
tokens. If the bot token rotates or multiple tokens are used in one
process, capabilities detected for token A would be returned for
token B, causing wrong schema gating and incorrect runtime behavior.
Replace the single Optional cache with a Dict keyed by token so each
token gets its own isolated capability entry.
_search_members() and _fetch_messages() call min(limit, 100) assuming
limit is int. Models can pass limit as a string (e.g. "10"), causing
TypeError: '<' not supported between instances of 'str' and 'int'.
Add try/except int() coercion with safe defaults at the top of both
functions, matching the pattern used in session_search fix (#10522).
Split the monolithic discord_server tool (14 actions) into two:
- discord: core actions (fetch_messages, search_members, create_thread)
that are useful for the agent's normal operation. Auto-enabled on
the discord platform via the pipeline fix.
- discord_admin: server management actions (list channels/roles, pins,
role assignment) that require explicit opt-in via hermes tools.
Added to CONFIGURABLE_TOOLSETS and _DEFAULT_OFF_TOOLSETS.
* feat: add Discord server introspection and management tool
Add a discord_server tool that gives the agent the ability to interact
with Discord servers when running on the Discord gateway. Uses Discord
REST API directly with the bot token — no dependency on the gateway
adapter's discord.py client.
The tool is only included in the hermes-discord toolset (zero cost for
users on other platforms) and gated on DISCORD_BOT_TOKEN via check_fn.
Actions (14):
- Introspection: list_guilds, server_info, list_channels, channel_info,
list_roles, member_info, search_members
- Messages: fetch_messages, list_pins, pin_message, unpin_message
- Management: create_thread, add_role, remove_role
This addresses a gap where users on Discord could not ask Hermes to
review server structure, channels, roles, or members — a task competing
agents (OpenClaw) handle out of the box.
Files changed:
- tools/discord_tool.py (new): Tool implementation + registration
- model_tools.py: Add to discovery list
- toolsets.py: Add to hermes-discord toolset only
- tests/tools/test_discord_tool.py (new): 43 tests covering all actions,
validation, error handling, registration, and toolset scoping
* feat(discord): intent-aware schema filtering + config allowlist + schema cleanup
- _detect_capabilities() hits GET /applications/@me once per process
to read GUILD_MEMBERS / MESSAGE_CONTENT privileged intent bits.
- Schema is rebuilt per-session in model_tools.get_tool_definitions:
hides search_members / member_info when GUILD_MEMBERS intent is off,
annotates fetch_messages description when MESSAGE_CONTENT is off.
- New config key discord.server_actions (comma-separated or YAML list)
lets users restrict which actions the agent can call, intersected
with intent availability. Unknown names are warned and dropped.
- Defense-in-depth: runtime handler re-checks the allowlist so a stale
cached schema cannot bypass a tightened config.
- Schema description rewritten as an action-first manifest (signature
per action) instead of per-parameter 'required for X, Y, Z' cross-refs.
~25% shorter; model can see each action's required params at a glance.
- Added bounds: limit gets minimum=1 maximum=100, auto_archive_duration
becomes an enum of the 4 valid Discord values.
- 403 enrichment: runtime 403 errors are mapped to actionable guidance
(which permission is missing and what to do about it) instead of the
raw Discord error body.
- 36 new tests: capability detection with caching and force refresh,
config allowlist parsing (string/list/invalid/unknown), intent+allowlist
intersection, dynamic schema build, runtime allowlist enforcement,
403 enrichment, and model_tools integration wiring.
