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Query the knowledge indexes: search by meaning, answer relationship questions with triple patterns, or list graph subjects by type. Use when you need ranked semantic results or graph relationships without standing up a vector database or SPARQL endpoint.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Prove whether a skill-pack change made agents better at writing code. Use when a single passing eval doesn't prove anything and you need multi-run pass@k evidence, when grading coding tasks with hidden tests the agent cannot see, or when comparing outcomes across skill-set versions.
Create design documents (WHICH/WHERE) for approved specs. A design is a max-200-line architectural sketch — components, interfaces, data flow, and key decisions with trade-offs — that gives reviewers a high-leverage point to redirect architecture before the full plan is written. Design is approved when `wiki/STATUS.md` shows the spec row at `design approved` — written there by a human signal that `kata-dispatch` or the active agent propagates.
Write implementation plans (HOW/WHEN) for approved designs. Translate an approved design into concrete steps, file changes, sequencing, and risks for a trusted agent to execute. Plan is approved when `wiki/STATUS.md` shows the spec row at `plan approved` — `staff-engineer` writes this row after a clean panel review (plans may be approved by agents).
Grade a single artifact (spec, design, plan, or implementation diff) against quality criteria and return findings by severity. Use when another skill spawns a fresh sub-agent for an independent review of its work. This skill never spawns sub-agents — it produces findings only — which structurally prevents the spec/design/plan/implement review loop from recursing.
Write specifications (WHAT/WHY) for features, changes, and improvements. Spec is approved when `wiki/STATUS.md` shows the spec row at `spec approved` — written there by a human signal (label, comment, APPROVED review, or in-session message) that `kata-dispatch` or the active agent propagates. Use when proposing changes, capturing findings as actionable specs, or evaluating spec quality. Pair with the `kata-plan` skill for the HOW side.
Merge gate for open pull requests. Verify contributor trust, classify PR type, rebase on main, fix mechanical CI failures, gate on `wiki/STATUS.md` approval state, and merge passing PRs. Sole external merge point.
| name | fit-rag |
| description | Query the knowledge indexes: search by meaning, answer relationship questions with triple patterns, or list graph subjects by type. Use when you need ranked semantic results or graph relationships without standing up a vector database or SPARQL endpoint. |
fit-rag is the read surface over the indexes the build pipeline produces. One
binary, three subcommands: search ranks a vector index by meaning, query
matches a triple pattern against a graph index, and subjects enumerates graph
subjects by type. Build the indexes first; this queries them.
fit-rag search 'career progression'fit-rag query "?" rdf:type schema:Personfit-rag subjects schema:Person# Semantic search — one result per line, identifier<TAB>score, top 10 by
# descending similarity. Calls the embedding service to vectorize the query.
fit-rag search 'career progression'
# Triple-pattern query — exactly three arguments (subject predicate object).
# Put `?` in the position to resolve; prints one matching identifier per line.
fit-rag query "?" rdf:type schema:Person
# Subject listing — one subject<TAB>type per line; pass a type to filter.
fit-rag subjects
fit-rag subjects schema:Person
search reads the vector index and needs the embedding service; query and
subjects read the graph index and run offline. Build and populate the indexes
first — see the guides below.