agentleFS
aptitude-stackaptitude-stack/registery/.agents/skills/task-doc-navigator/SKILL.md

task-doc-navigator

Skill1 starsChanged 8 months agoMITView on GitHub

Navigate Aptitude tasks by using `.agents/agent.md` as the entrypoint, especially its Task-to-Doc Map and relevant path lists, to gather the smallest set of sources needed for implementation, review, debugging, planning, or documentation work. Use when Codex should identify the most relevant docs, plans, changelogs, tests, and code paths before acting on a task.

The file

We split this skill into the rules it gives an agent

11 rules. About 0 are common, 6 are distinctive, and 5 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈6

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 5

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use .agents/agent.md as the primary navigation contract.

    line 8
  2. Distinctive:

    If the task touches behavior, check the matching tests, active plan file, and prior changelog entries before editing.

    line 22
  3. Distinctive:

    Start small and add sources only when they change the decision.

    line 26
  4. Very specific:

    Use the path lists in .agents/agent.md to jump to the smallest likely module:

    line 85
  5. Distinctive:

    Use this compact format:

    line 105
  6. Distinctive:

    Prefer the smallest relevant set of files over broad repo scans.

    line 117
  7. Very specific:

    Read rules/repo.md when approval gates, repo rules, or process constraints may matter.

    line 118
  8. Very specific:

    If a task clearly maps to one section in .agents/agent.md, do not open unrelated docs “just in case”.

    line 119
  9. Distinctive:

    If the task spans multiple areas, load sources in this order: rules, active plan, task-mapped docs, code paths, tests, changelog.

    line 120
  10. Distinctive:

    When reporting file references or source maps, use repo-relative paths or GitHub links only.

    line 121
  11. Very specific:

    Never emit workstation-specific absolute paths such as /path/to/repo/....

    line 122

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Task Doc Navigator

Use .agents/agent.md as the primary navigation contract.

Workflow

  1. Read .agents/agent.md first.
  2. Classify the task before opening more files:
    • architecture or product intent
    • API or contract behavior
    • persistence, discovery, or schema work
    • milestone delivery history
    • implementation in a specific module
    • verification or test failure
  3. Open only the matching docs from the Task-to-Doc Map and Relevant Paths for Task Execution.
  4. Expand into code only after the minimal doc set is loaded.
  5. If the task touches behavior, check the matching tests, active plan file, and prior changelog entries before editing.

Source Selection

Start small and add sources only when they change the decision.

Architecture and scope

Open:

  • docs/architecture/system-overview.md
  • docs/architecture/server-resolver-boundary.md
  • docs/roadmap/aptitude-registry-prd.md

Use for:

  • new features
  • boundary questions
  • architecture tradeoffs
  • requirement clarification

API and contract work

Open:

  • docs/reference/api-contract.md
  • postman/collections/
  • app/interface/
  • relevant integration tests in tests/integration/

Use for:

  • endpoint behavior
  • request or response shape
  • error mapping
  • manual validation flows

Persistence and discovery

Open:

  • docs/reference/schema.md
  • docs/reference/storage-strategy.md
  • docs/architecture/discovery-and-ranking.md
  • app/persistence/
  • alembic/versions/

Use for:

  • schema or migration changes
  • repository behavior
  • ranking, filtering, or candidate selection

Delivery history and sequencing

Open:

  • active .agents/plans/XX-*.md
  • .agents/plans/roadmap.md
  • docs/changelog/
  • memory/meta.md

Use for:

  • milestone alignment
  • acceptance criteria
  • earlier design decisions
  • avoiding duplicate work

Code-path lookup

Use the path lists in .agents/agent.md to jump to the smallest likely module:

  • app/main.py for composition and wiring
  • app/interface/ for routes and DTOs
  • app/core/ for domain logic and governance
  • app/intelligence/ for ranking and search logic
  • app/persistence/ for models and repositories
  • app/audit/ for audit-facing behavior

Verification lookup

Open only the matching verification surface:

  • tests/unit/ for pure logic and service behavior
  • tests/integration/ for API, repository, and migration behavior
  • .github/workflows/ for CI command patterns
  • scripts/ when repo tooling is part of the task

Output

Report the source map before substantial implementation when the task is non-trivial.

Use this compact format:

Task class: <one line>
Primary docs: <paths>
Primary code paths: <paths>
Verification paths: <paths>
Deferred sources: <paths not opened yet>

Guardrails

  • Prefer the smallest relevant set of files over broad repo scans.
  • Read rules/repo.md when approval gates, repo rules, or process constraints may matter.
  • If a task clearly maps to one section in .agents/agent.md, do not open unrelated docs “just in case”.
  • If the task spans multiple areas, load sources in this order: rules, active plan, task-mapped docs, code paths, tests, changelog.
  • When reporting file references or source maps, use repo-relative paths or GitHub links only.
  • Never emit workstation-specific absolute paths such as /path/to/repo/....

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.