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AC sifs-search

Use this skill when you need to find code in a local checkout or Git source by behavior, intent, symbol, file path, related implementation, or indexed chunk context. Use it before broad file reads or grep-style sweeps for exploratory codebase questions, architecture tracing, call-site discovery, and "where/how is X implemented?" tasks. Do not use it for general web search or non-code files unless the user asks to search a source tree.

ClawHub Agent Skills author: Tristan Manchester v0.1.0 MIT-0 6 files · 1 script body ≈ 466 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
99
Quality 40%
92
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Concealment en-hide-from-user references/troubleshooting.md:26
      Instruction to hide actions from the user (negated — the text forbids it)
      If neither installer is available, report that SIFS is missing and continue with the agent's normal code-search tools. Do not silently install system packages unless the user or local project instruct
      negated

    Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 60/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 7 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 466 tokens
    • 100Running it twice. No mutating operations

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Structure: 1 headings, hard to scan
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 438: enough signal without eating the budget
    • +3Step-by-step instructions: 7 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: clean
    The inspected skills are coherent developer and ClawHub operations helpers, with sensitive actions mostly disclosed and guarded by user-directed workflows.
    LLM: benign (medium) · VirusTotal: · 29 May 2026