SKILLEMALL.ai

AC code-research-crafter

Research codebases and craft professional RFC proposals for GitHub publication. Use when: user wants to analyze a codebase and propose enhancements, write an RFC, research a technical problem with academic rigor, design an architecture proposal, submit a proposal to an open-source project, or create a structured improvement plan. NOT for: simple code reviews, bug fixing, general Q&A, quick code searches, or one-off questions.

ClawHub Agent Skills author: ZhangYuanzhuo v1.1.0 MIT-0 8 files body ≈ 1 772 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 62/100 · Has gaps — weak spots: inputs and preconditions, running it twice, progress reporting

AnalyzerGitHubSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
95
Quality 40%
96
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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
    • medium Exfiltration net-credential-use SKILL.md:132
      Credential used in a network call (verify the destination is the intended service)
      curl -X POST -H "Authorization: token $GITHUB_TOKEN" \

    Files scanned: 8. 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 62/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Failures and branches. 9 branches
    • 100Steps. 60 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1772 tokens

    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
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 429: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 60 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.

    External checks

    ClawHub: suspicious
    This skill is coherent and instruction-only, but it can publish code-research output to GitHub through the user's account without a clear final approval and privacy check.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026