* 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.
115 lines
5.7 KiB
Markdown
115 lines
5.7 KiB
Markdown
---
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title: "One Three One Rule — Structured decision-making framework for technical proposals and trade-off analysis"
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sidebar_label: "One Three One Rule"
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description: "Structured decision-making framework for technical proposals and trade-off analysis"
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---
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{/* 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. */}
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# One Three One Rule
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Structured decision-making framework for technical proposals and trade-off analysis. When the user faces a choice between multiple approaches (architecture decisions, tool selection, refactoring strategies, migration paths), this skill produces a 1-3-1 format: one clear problem statement, three distinct options with pros/cons, and one concrete recommendation with definition of done and implementation plan. Use when the user asks for a "1-3-1", says "give me options", or needs help choosing between competing approaches.
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## Skill metadata
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| Source | Optional — install with `hermes skills install official/communication/one-three-one-rule` |
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| Path | `optional-skills/communication/one-three-one-rule` |
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| Version | `1.0.0` |
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| Author | Willard Moore |
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| License | MIT |
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| Platforms | linux, macos, windows |
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| Tags | `communication`, `decision-making`, `proposals`, `trade-offs` |
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## Reference: full SKILL.md
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:::info
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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.
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:::
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# 1-3-1 Communication Rule
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Structured decision-making format for when a task has multiple viable approaches and the user needs a clear recommendation. Produces a concise problem framing, three options with trade-offs, and an actionable plan for the recommended path.
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## When to Use
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- The user explicitly asks for a "1-3-1" response.
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- The user says "give me options" or "what are my choices" for a technical decision.
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- A task has multiple viable approaches with meaningful trade-offs (architecture, tooling, migration strategy).
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- The user needs a proposal they can forward to a team or stakeholder.
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Do NOT use for simple questions with one obvious answer, debugging sessions, or tasks where the user has already decided on an approach.
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## Procedure
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1. **Problem** (one sentence)
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- State the core decision or desired outcome in a single concise sentence.
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- Focus on the *what*, not the *how* — no implementation details, tool names, or specific technologies.
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- Keep it tight. If you need "and", you're describing two problems.
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2. **Options** (exactly three)
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- Present three distinct, viable approaches labeled A, B, C.
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- Each option gets a brief description, pros, and cons.
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- Options should represent genuinely different strategies, not minor variations of the same approach.
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3. **Recommendation** (one option)
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- State which option you recommend and why, based on the user's context and priorities.
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- Be direct — this is your professional judgment, not a hedge.
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4. **Definition of Done**
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- List the specific success criteria for the recommended option.
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- These are concrete, verifiable outcomes — not vague aspirations.
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- If the user picks a different option, revise this section to match.
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5. **Implementation Plan**
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- Concrete steps to execute the recommended option.
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- Include specific commands, tools, or actions where applicable.
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- If the user picks a different option, revise this section to match.
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## Verification
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- Response has exactly one Problem sentence.
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- Response has exactly three Options (A, B, C) with pros and cons for each.
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- Response has a single Recommendation that picks one option with reasoning.
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- Definition of Done and Implementation Plan align with the recommended option.
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- If the user selects a different option, Recommendation, DoD, and Implementation Plan update accordingly.
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## Example
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User: "Give me a 1-3-1 for adding retry logic to our API client."
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Agent:
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**Problem:** API calls to external services fail intermittently under load and need graceful retry handling.
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**Options:**
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- **Option A: Exponential backoff with jitter in a shared utility.**
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Pros: Simple, well-understood pattern; single implementation shared across all callers.
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Cons: No circuit-breaking; callers still block during retries.
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- **Option B: Retry library (tenacity) as a decorator on each endpoint call.**
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Pros: Configurable per-endpoint; built-in support for circuit breakers and rate limits.
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Cons: Adds a dependency; decorator pattern can obscure control flow.
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- **Option C: Queue-based async retry with dead letter handling.**
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Pros: Non-blocking; failed calls are tracked and replayable; scales well.
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Cons: Significant complexity increase; requires a queue backend; overkill for low-volume services.
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**Recommendation:** Option A. The call volume doesn't justify queue infrastructure, and a shared utility with exponential backoff + jitter covers the failure mode cleanly without new dependencies.
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**Definition of Done:**
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- `api_retry()` utility handles transient HTTP errors (429, 502, 503, 504).
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- Retries up to 3 times with exponential backoff and jitter.
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- All external API calls route through the retry utility.
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- Logs each retry attempt with endpoint and attempt number.
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- Tests cover retry exhaustion, immediate success, and transient-then-success scenarios.
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**Implementation Plan:**
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1. Create `utils/api_retry.py` with configurable max retries, base delay, and retryable status codes.
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2. Add jitter using `random.uniform(0, base_delay)` to prevent thundering herd.
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3. Wrap existing API calls in `api_client.py` with the retry utility.
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4. Add unit tests mocking HTTP responses for each retry scenario.
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5. Verify under load with a simple stress test against a flaky endpoint mock.
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