Technical Documentation

Technical Documentation

Purpose

Produce and review technical documentation that is clear, actionable, and maintainable for both humans and agents, including contributor-governance files and agent instruction files.

When to use

• Creating or overhauling docs in an existing product/codebase (brownfield).
• Building evergreen docs meant to stay accurate and reusable over time.
• Reviewing doc diffs for structure, clarity, and operational correctness.
• Running full-repo documentation audits that must include both governance files and product docs surfaces (docs/, README*, .md/.mdx/.mdc, Fern/Sphinx/Mintlify-style sources).
• Updating or reviewing AGENTS.md and/or CONTRIBUTING.md to keep agent and contributor workflows aligned with current repo practices.
• Improving repository onboarding/docs that include contribution instructions, issue templates, PR flow, and review gates.
• Designing governance documentation strategy for repos with alias instruction files (for example CLAUDE.md, AGENT.md, .cursorrules, .cursor/rules/*, .agent/, .agents/, .pi/) where CLAUDE.md is treated as a canonical policy source and AGENTS.md should be kept as compatibility alias if present.
• Diagnosing agent-file drift where teams had to prompt iteratively to surface missing files, broken commands, or policy conflicts.

Workflow

1. Classify task: build or review; context: brownfield or evergreen.
2. Inventory full documentation scope early (governance + product docs): AGENTS/CONTRIBUTING/aliases plus docs directories, framework sources, and root/module READMEs.
3. Detect multilingual scope (README/docs in multiple languages) and define required parity level.
4. Read references/agent-and-contributing.md for agent instruction and CONTRIBUTING.md workflow rules (inventory, canonical/alias mapping, dual-mode balance, deliverable standards, and precedence/conflict handling).
5. Read references/principles.md for the governing ruleset (Matt Palmer & OpenAI).
6. For build tasks, follow references/build.md.
7. For review tasks, follow references/review.md and proactively detect issues without waiting for repeated prompts.
8. For complex or high-risk tasks (build or review), it is acceptable to run longer, deeper, and more exhaustive investigations when needed for confidence.
9. When available, use sub-agents for bounded parallel discovery/review work, then merge outputs into one coherent final deliverable.
10. Use references/tooling.md when platform/tooling choices affect recommendations.
11. Run a proactive issue sweep for both governance and docs-content surfaces, and fix high-confidence defects in the same pass unless explicitly asked for report-only mode.
12. In brownfield mode, prioritize compatibility with current docs IA, tooling, and release state.
13. In evergreen mode, prioritize timeless wording, update strategy, and durable structure.
14. Return deliverables plus validation notes, parity status, and remaining gaps.

Sub-agent orchestration guidance

Prefer sub-agents when the repo is large or the requested change set is broad; use them by default for repo-wide, multi-framework, or high-conflict work.

• inventory-agent -> agents/inventory-agent.md (fast / Claude haiku): file/config discovery, coverage map, and missing-path checks.
• governance-agent -> agents/governance-agent.md (thinking / Claude sonnet): AGENTS/CONTRIBUTING/alias precedence, conflicts, and policy drift.
• docs-framework-agent -> agents/docs-framework-agent.md (thinking / Claude sonnet): framework config, relative path base, and file-path vs URL-path mapping checks.
• synthesis-agent -> agents/synthesis-agent.md (long / Claude opus): merge sub-agent outputs into one prioritized fix plan and unified precedence model.

Inputs

• Doc type (tutorial, how-to, reference, explanation) and audience.
• File scope or diff scope.
• Docs framework/tooling constraints (Fern, Mintlify, Sphinx, etc.).
• Build/review mode and brownfield/evergreen intent.
• Target agent and human compatibility intent.
• Docs framework surfaces in scope (for example Fern, Sphinx, Mintlify, Markdown/MDX/MDC/RST/RSC files).
• Desired investigation depth/time budget (quick pass vs exhaustive review).
• Execution mode (single-agent or sub-agent-assisted when available).
• Remediation mode (apply-fixes by default, or report-only when requested).
• Multilingual scope: source-of-truth language, target locales, and parity expectations.

Outputs

• Updated draft or review findings with clear next actions.
• Validation notes (what was checked, what remains).
• Navigation/maintenance recommendations for long-term quality.
• Governance-doc alignment summary when AGENTS/CONTRIBUTING were touched.
• Agent instruction-surface map (primary file, alias files, Codex/Claude/Cursor handling plan).
• Documentation-surface coverage map (what was reviewed under /docs, README hierarchy, and framework-specific source trees).
• Autodetected issue list with applied fixes (or explicit report-only findings).
• Delegation notes when sub-agents were used (scope delegated and how findings were merged).
• Multilingual parity note (in-sync, partial with rationale, or intentionally divergent).