agentleFS
mycelium-hqmycelium-hq/ai-brain-starter/skills/resolver-query/SKILL.md

resolver-query

Skill50 starsChanged 7 months agoMITView on GitHub

Use when an operator asks which rule or policy governs a question — pricing exceptions, deploys, refunds, hiring — or wants to look up the matching rule in Meta/RESOLVER.md without reading the whole index by hand. Triggers: /resolver-query <question>, "which rule applies", "what''s our policy on X", "does a rule cover this". Not for writing or editing rules (read-only) and not for rebuilding RESOLVER.md (use resolver-build.py).

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    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. Very specific:

    When match_kind == none, the skill returns the empty matched_rules list and the host session tells the operator no rule matches.

    line 101

≈ “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

/resolver-query

Look up which rule in Meta/RESOLVER.md applies to a natural-language question. The skill itself does NOT call an LLM. It reads RESOLVER.md, parses every rule row, and returns either a decisive match, a ranked candidate list, or "no rule matches." The host Claude session does the natural-language understanding on top of the structured output.

When to run

  • An operator wonders which rule governs a recurring question (pricing, deploy, refund, hiring exception).
  • A new teammate wants to find the policy for a scenario without reading the full resolver index.
  • Any time the resolver layer should answer a query and the operator wants the structured candidate set in one call.

How it works

  1. The skill reads Meta/RESOLVER.md from the vault root.
  2. It parses the YAML frontmatter for the build timestamp and counts.
  3. It parses every row of the ## Rules table into a structured record.
  4. It runs a deterministic match against the question: a. Tokenize the question (lowercase, drop stopwords, keep stems). b. For each rule, score by token overlap against rule_id, source path, skill link, and source-file H1/topic when available. c. If exactly one rule scores >= the decisive threshold, return that rule directly. d. Otherwise return up to --limit rules ranked by score. e. If no rule scores above zero, return no rule matches this query.
  5. The host session then reads the structured output and frames the answer to the operator.

Step 1: Run the skill

python3 skills/resolver-query/query.py "How do we handle pricing exceptions?" \
    --vault-root <vault>

Output is a JSON document on stdout with shape:

{
  "question": "...",
  "vault_root": "...",
  "resolver_built_at": "...",
  "rule_count": 17,
  "match_kind": "decisive | ranked | none",
  "matched_rules": [
    {
      "rule_id": "...",
      "type": "decision | workflow | exception | fact",
      "status": "active | stale | superseded | under-review | unknown",
      "last_verified": "...",
      "source_path": "...",
      "skill_link": "...",
      "score": 0.0
    }
  ],
  "summary": "..."
}

Step 2: Read the matched rule

If the match kind is decisive, the host session opens the rule's source file (source_path). If ranked, the host session presents the top candidates to the operator and lets them pick. If none, the host session tells the operator no rule applies and offers to draft one manually.

Rules

  • The skill is read-only. It NEVER writes to RESOLVER.md or any source file.
  • The skill makes no external network calls. No LLM API is invoked from inside query.py.
  • The matching algorithm is deterministic and stdlib-only. The host Claude session is the natural-language layer on top.
  • When match_kind == none, the skill returns the empty matched_rules list and the host session tells the operator no rule matches; it does not invent one.

Boundary

  • Adjacent skills:
    • scripts/resolver-build.py rebuilds RESOLVER.md.
    • scripts/resolver-conflict-report.py surfaces conflicts in JSON.
    • scripts/resolver-branch-merge-prompt.py drafts merge prompts.
  • This skill READS the rendered index. It does not refresh, edit, or rewrite it.

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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.