* docs: deep audit — fix stale config keys, missing commands, and registry drift Cross-checked ~80 high-impact docs pages (getting-started, reference, top-level user-guide, user-guide/features) against the live registries: hermes_cli/commands.py COMMAND_REGISTRY (slash commands) hermes_cli/auth.py PROVIDER_REGISTRY (providers) hermes_cli/config.py DEFAULT_CONFIG (config keys) toolsets.py TOOLSETS (toolsets) tools/registry.py get_all_tool_names() (tools) python -m hermes_cli.main <subcmd> --help (CLI args) reference/ - cli-commands.md: drop duplicate hermes fallback row + duplicate section, add stepfun/lmstudio to --provider enum, expand auth/mcp/curator subcommand lists to match --help output (status/logout/spotify, login, archive/prune/ list-archived). - slash-commands.md: add missing /sessions and /reload-skills entries + correct the cross-platform Notes line. - tools-reference.md: drop bogus '68 tools' headline, drop fictional 'browser-cdp toolset' (these tools live in 'browser' and are runtime-gated), add missing 'kanban' and 'video' toolset sections, fix MCP example to use the real mcp_<server>_<tool> prefix. - toolsets-reference.md: list browser_cdp/browser_dialog inside the 'browser' row, add missing 'kanban' and 'video' toolset rows, drop the stale '38 tools' count for hermes-cli. - profile-commands.md: add missing install/update/info subcommands, document fish completion. - environment-variables.md: dedupe GMI_API_KEY/GMI_BASE_URL rows (kept the one with the correct gmi-serving.com default). - faq.md: Anthropic/Google/OpenAI examples — direct providers exist (not just via OpenRouter), refresh the OpenAI model list. getting-started/ - installation.md: PortableGit (not MinGit) is what the Windows installer fetches; document the 32-bit MinGit fallback. - installation.md / termux.md: installer prefers .[termux-all] then falls back to .[termux]. - nix-setup.md: Python 3.12 (not 3.11), Node.js 22 (not 20); fix invalid 'nix flake update --flake' invocation. - updating.md: 'hermes backup restore --state pre-update' doesn't exist — point at the snapshot/quick-snapshot flow; correct config key 'updates.pre_update_backup' (was 'update.backup'). user-guide/ - configuration.md: api_max_retries default 3 (not 2); display.runtime_footer is the real key (not display.runtime_metadata_footer); checkpoints defaults enabled=false / max_snapshots=20 (not true / 50). - configuring-models.md: 'hermes model list' / 'hermes model set ...' don't exist — hermes model is interactive only. - tui.md: busy_indicator -> tui_status_indicator with values kaomoji|emoji|unicode|ascii (not kawaii|minimal|dots|wings|none). - security.md: SSH backend keys (TERMINAL_SSH_HOST/USER/KEY) live in .env, not config.yaml. - windows-wsl-quickstart.md: there is no 'hermes api' subcommand — the OpenAI-compatible API server runs inside hermes gateway. user-guide/features/ - computer-use.md: approvals.mode (not security.approval_level); fix broken ./browser-use.md link to ./browser.md. - fallback-providers.md: top-level fallback_providers (not model.fallback_providers); the picker is subcommand-based, not modal. - api-server.md: API_SERVER_* are env vars — write to per-profile .env, not 'hermes config set' which targets YAML. - web-search.md: drop web_crawl as a registered tool (it isn't); deep-crawl modes are exposed through web_extract. - kanban.md: failure_limit default is 2, not '~5'. - plugins.md: drop hard-coded '33 providers' count. - honcho.md: fix unclosed quote in echo HONCHO_API_KEY snippet; document that 'hermes honcho' subcommand is gated on memory.provider=honcho; reconcile subcommand list with actual --help output. - memory-providers.md: legacy 'hermes honcho setup' redirect documented. Verified via 'npm run build' — site builds cleanly; broken-link count went from 149 to 146 (no regressions, fixed a few in passing). * docs: round 2 audit fixes + regenerate skill catalogs Follow-up to the previous commit on this branch: Round 2 manual fixes: - quickstart.md: KIMI_CODING_API_KEY mentioned alongside KIMI_API_KEY; voice-mode and ACP install commands rewritten — bare 'pip install ...' doesn't work for curl-installed setups (no pip on PATH, not in repo dir); replaced with 'cd ~/.hermes/hermes-agent && uv pip install -e ".[voice]"'. ACP already ships in [all] so the curl install includes it. - cli.md / configuration.md: 'auxiliary.compression.model' shown as 'google/gemini-3-flash-preview' (the doc's own claimed default); actual default is empty (= use main model). Reworded as 'leave empty (default) or pin a cheap model'. - built-in-plugins.md: added the bundled 'kanban/dashboard' plugin row that was missing from the table. Regenerated skill catalogs: - ran website/scripts/generate-skill-docs.py to refresh all 163 per-skill pages and both reference catalogs (skills-catalog.md, optional-skills-catalog.md). This adds the entries that were genuinely missing — productivity/teams-meeting-pipeline (bundled), optional/finance/* (entire category — 7 skills: 3-statement-model, comps-analysis, dcf-model, excel-author, lbo-model, merger-model, pptx-author), creative/hyperframes, creative/kanban-video-orchestrator, devops/watchers, productivity/shop-app, research/searxng-search, apple/macos-computer-use — and rewrites every other per-skill page from the current SKILL.md. Most diffs are tiny (one line of refreshed metadata). Validation: - 'npm run build' succeeded. - Broken-link count moved 146 -> 155 — the +9 are zh-Hans translation shells that lag every newly-added skill page (pre-existing pattern). No regressions on any en/ page.
12 KiB
| title | sidebar_label | description |
|---|---|---|
| Parallel Cli | Parallel Cli | Optional vendor skill for Parallel CLI — agent-native web search, extraction, deep research, enrichment, FindAll, and monitoring |
{/* This page is auto-generated from the skill's SKILL.md by website/scripts/generate-skill-docs.py. Edit the source SKILL.md, not this page. */}
Parallel Cli
Optional vendor skill for Parallel CLI — agent-native web search, extraction, deep research, enrichment, FindAll, and monitoring. Prefer JSON output and non-interactive flows.
Skill metadata
| Source | Optional — install with hermes skills install official/research/parallel-cli |
| Path | optional-skills/research/parallel-cli |
| Version | 1.1.0 |
| Author | Hermes Agent |
| License | MIT |
| Platforms | linux, macos, windows |
| Tags | Research, Web, Search, Deep-Research, Enrichment, CLI |
| Related skills | duckduckgo-search, mcporter |
Reference: full SKILL.md
:::info The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active. :::
Parallel CLI
Use parallel-cli when the user explicitly wants Parallel, or when a terminal-native workflow would benefit from Parallel's vendor-specific stack for web search, extraction, deep research, enrichment, entity discovery, or monitoring.
This is an optional third-party workflow, not a Hermes core capability.
Important expectations:
- Parallel is a paid service with a free tier, not a fully free local tool.
- It overlaps with Hermes native
web_search/web_extract, so do not prefer it by default for ordinary lookups. - Prefer this skill when the user mentions Parallel specifically or needs capabilities like Parallel's enrichment, FindAll, or monitor workflows.
parallel-cli is designed for agents:
- JSON output via
--json - Non-interactive command execution
- Async long-running jobs with
--no-wait,status, andpoll - Context chaining with
--previous-interaction-id - Search, extract, research, enrichment, entity discovery, and monitoring in one CLI
When to use it
Prefer this skill when:
- The user explicitly mentions Parallel or
parallel-cli - The task needs richer workflows than a simple one-shot search/extract pass
- You need async deep research jobs that can be launched and polled later
- You need structured enrichment, FindAll entity discovery, or monitoring
Prefer Hermes native web_search / web_extract for quick one-off lookups when Parallel is not specifically requested.
Installation
Try the least invasive install path available for the environment.
Homebrew
brew install parallel-web/tap/parallel-cli
npm
npm install -g parallel-web-cli
Python package
pip install "parallel-web-tools[cli]"
Standalone installer
curl -fsSL https://parallel.ai/install.sh | bash
If you want an isolated Python install, pipx can also work:
pipx install "parallel-web-tools[cli]"
pipx ensurepath
Authentication
Interactive login:
parallel-cli login
Headless / SSH / CI:
parallel-cli login --device
API key environment variable:
export PARALLEL_API_KEY="***"
Verify current auth status:
parallel-cli auth
If auth requires browser interaction, run with pty=true.
Core rule set
- Always prefer
--jsonwhen you need machine-readable output. - Prefer explicit arguments and non-interactive flows.
- For long-running jobs, use
--no-waitand thenstatus/poll. - Cite only URLs returned by the CLI output.
- Save large JSON outputs to a temp file when follow-up questions are likely.
- Use background processes only for genuinely long-running workflows; otherwise run in foreground.
- Prefer Hermes native tools unless the user wants Parallel specifically or needs Parallel-only workflows.
Quick reference
parallel-cli
├── auth
├── login
├── logout
├── search
├── extract / fetch
├── research run|status|poll|processors
├── enrich run|status|poll|plan|suggest|deploy
├── findall run|ingest|status|poll|result|enrich|extend|schema|cancel
└── monitor create|list|get|update|delete|events|event-group|simulate
Common flags and patterns
Commonly useful flags:
--jsonfor structured output--no-waitfor async jobs--previous-interaction-id <id>for follow-up tasks that reuse earlier context--max-results <n>for search result count--mode one-shot|agenticfor search behavior--include-domains domain1.com,domain2.com--exclude-domains domain1.com,domain2.com--after-date YYYY-MM-DD
Read from stdin when convenient:
echo "What is the latest funding for Anthropic?" | parallel-cli search - --json
echo "Research question" | parallel-cli research run - --json
Search
Use for current web lookups with structured results.
parallel-cli search "What is Anthropic's latest AI model?" --json
parallel-cli search "SEC filings for Apple" --include-domains sec.gov --json
parallel-cli search "bitcoin price" --after-date 2026-01-01 --max-results 10 --json
parallel-cli search "latest browser benchmarks" --mode one-shot --json
parallel-cli search "AI coding agent enterprise reviews" --mode agentic --json
Useful constraints:
--include-domainsto narrow trusted sources--exclude-domainsto strip noisy domains--after-datefor recency filtering--max-resultswhen you need broader coverage
If you expect follow-up questions, save output:
parallel-cli search "latest React 19 changes" --json -o /tmp/react-19-search.json
When summarizing results:
- lead with the answer
- include dates, names, and concrete facts
- cite only returned sources
- avoid inventing URLs or source titles
Extraction
Use to pull clean content or markdown from a URL.
parallel-cli extract https://example.com --json
parallel-cli extract https://company.com --objective "Find pricing info" --json
parallel-cli extract https://example.com --full-content --json
parallel-cli fetch https://example.com --json
Use --objective when the page is broad and you only need one slice of information.
Deep research
Use for deeper multi-step research tasks that may take time.
Common processor tiers:
lite/basefor faster, cheaper passescore/profor more thorough synthesisultrafor the heaviest research jobs
Synchronous
parallel-cli research run \
"Compare the leading AI coding agents by pricing, model support, and enterprise controls" \
--processor core \
--json
Async launch + poll
parallel-cli research run \
"Compare the leading AI coding agents by pricing, model support, and enterprise controls" \
--processor ultra \
--no-wait \
--json
parallel-cli research status trun_xxx --json
parallel-cli research poll trun_xxx --json
parallel-cli research processors --json
Context chaining / follow-up
parallel-cli research run "What are the top AI coding agents?" --json
parallel-cli research run \
"What enterprise controls does the top-ranked one offer?" \
--previous-interaction-id trun_xxx \
--json
Recommended Hermes workflow:
- launch with
--no-wait --json - capture the returned run/task ID
- if the user wants to continue other work, keep moving
- later call
statusorpoll - summarize the final report with citations from the returned sources
Enrichment
Use when the user has CSV/JSON/tabular inputs and wants additional columns inferred from web research.
Suggest columns
parallel-cli enrich suggest "Find the CEO and annual revenue" --json
Plan a config
parallel-cli enrich plan -o config.yaml
Inline data
parallel-cli enrich run \
--data '[{"company": "Anthropic"}, {"company": "Mistral"}]' \
--intent "Find headquarters and employee count" \
--json
Non-interactive file run
parallel-cli enrich run \
--source-type csv \
--source companies.csv \
--target enriched.csv \
--source-columns '[{"name": "company", "description": "Company name"}]' \
--intent "Find the CEO and annual revenue"
YAML config run
parallel-cli enrich run config.yaml
Status / polling
parallel-cli enrich status <task_group_id> --json
parallel-cli enrich poll <task_group_id> --json
Use explicit JSON arrays for column definitions when operating non-interactively. Validate the output file before reporting success.
FindAll
Use for web-scale entity discovery when the user wants a discovered dataset rather than a short answer.
parallel-cli findall run "Find AI coding agent startups with enterprise offerings" --json
parallel-cli findall run "AI startups in healthcare" -n 25 --json
parallel-cli findall status <run_id> --json
parallel-cli findall poll <run_id> --json
parallel-cli findall result <run_id> --json
parallel-cli findall schema <run_id> --json
This is a better fit than ordinary search when the user wants a discovered set of entities that can be reviewed, filtered, or enriched later.
Monitor
Use for ongoing change detection over time.
parallel-cli monitor list --json
parallel-cli monitor get <monitor_id> --json
parallel-cli monitor events <monitor_id> --json
parallel-cli monitor delete <monitor_id> --json
Creation is usually the sensitive part because cadence and delivery matter:
parallel-cli monitor create --help
Use this when the user wants recurring tracking of a page or source rather than a one-time fetch.
Recommended Hermes usage patterns
Fast answer with citations
- Run
parallel-cli search ... --json - Parse titles, URLs, dates, excerpts
- Summarize with inline citations from the returned URLs only
URL investigation
- Run
parallel-cli extract URL --json - If needed, rerun with
--objectiveor--full-content - Quote or summarize the extracted markdown
Long research workflow
- Run
parallel-cli research run ... --no-wait --json - Store the returned ID
- Continue other work or periodically poll
- Summarize the final report with citations
Structured enrichment workflow
- Inspect the input file and columns
- Use
enrich suggestor provide explicit enriched columns - Run
enrich run - Poll for completion if needed
- Validate the output file before reporting success
Error handling and exit codes
The CLI documents these exit codes:
0success2bad input3auth error4API error5timeout
If you hit auth errors:
- check
parallel-cli auth - confirm
PARALLEL_API_KEYor runparallel-cli login/parallel-cli login --device - verify
parallel-cliis onPATH
Maintenance
Check current auth / install state:
parallel-cli auth
parallel-cli --help
Update commands:
parallel-cli update
pip install --upgrade parallel-web-tools
parallel-cli config auto-update-check off
Pitfalls
- Do not omit
--jsonunless the user explicitly wants human-formatted output. - Do not cite sources not present in the CLI output.
loginmay require PTY/browser interaction.- Prefer foreground execution for short tasks; do not overuse background processes.
- For large result sets, save JSON to
/tmp/*.jsoninstead of stuffing everything into context. - Do not silently choose Parallel when Hermes native tools are already sufficient.
- Remember this is a vendor workflow that usually requires account auth and paid usage beyond the free tier.