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jhonatan-oliveiradevjhonatan-oliveiradev/agent-skills/skills/investigating-codebase-semantically/SKILL.md

investigating-codebase-semantically

Skill1 starsChanged 3 months agoMITView on GitHub

Use when you need to locate the implementation of a behavior by intent and validate its ownership in code.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 4 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Ask one narrow structural question, define its scope, and state the decision it supports.

    line 14
  2. Distinctive:

    Use the narrowest symbol, relation, or targeted search that can answer the question.

    line 16
  3. Distinctive:

    Use an explicit fallback when runtime evidence is unavailable or inconclusive: inspect targeted symbols, search, imports, references, …

    line 17
  4. Very specific:

    Keep an evidence ledger for every material claim: claim, status (observed, inferred, or unresolved), source, location, confidence, and …

    line 18
  5. Distinctive:

    Stop at sufficiency when traceable evidence answers the question, critical dependencies are checked, gaps are classified, and further …

    line 19

≈ “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

Ownership

Find behavior by intent, then validate candidates in code instead of treating a textual match as ownership.

The workflow below implements the shared Codebase Intelligence evidence contract.

Workflow

  1. Ask one narrow structural question, define its scope, and state the decision it supports.
  2. Detect whether an optional code-intelligence runtime is available through callable tools only. Do not install a runtime, do not run codegraph init, and do not create .codegraph/ without explicit authorization.
  3. Use the narrowest symbol, relation, or targeted search that can answer the question; expand only to close a named evidence gap.
  4. Use an explicit fallback when runtime evidence is unavailable or inconclusive: inspect targeted symbols, search, imports, references, tests, configuration, and direct reads. A textual match is not proof of a caller, callee, or owner.
  5. Keep an evidence ledger for every material claim: claim, status (observed, inferred, or unresolved), source, location, confidence, and relevance.
  6. Stop at sufficiency when traceable evidence answers the question, critical dependencies are checked, gaps are classified, and further reading is unlikely to change the immediate decision. Hand off to the next owner.

Output contract

  • behavioral question;
  • search concepts;
  • candidate implementations;
  • validation evidence;
  • rejected false positives;
  • selected owner or unresolved ambiguity;
  • source references;

Does not own

Generic file lookup or unvalidated search results; a textual match can be a false positive and does not establish ownership.

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