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AC paper-code-joint-analysis

Jointly analyze a research paper and its open-source implementation. Use when a user wants to understand a paper through code, map theory/formulas/algorithms/experiments to real classes and methods, identify implementation details not disclosed in the paper, produce reproducibility commands and gaps, build explanatory diagrams or a static reader, or validate that an analysis covers both the paper and repository.

ClawHub Agent Skills author: c-narcissus v1.0.9 MIT-0 21 files body ≈ 4 029 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 60/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

AnalyzerSoftware 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
95/100
safety, quality, tests
Safety 60%
99
Quality 40%
90
Run on models
none yet
Process rating
C
60/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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 Secrets in code secret-high-entropy-token assets/reader-template/vendor/katex/katex.min.js:1
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      !function(e,t){"object"==typeof exports&&"object"==typeof module?module.exports=t():"function"==typeof define&&define.amd?define([],t):"object"==typeof exports?exports.katex=t():e.katex=t()}("undefine
      detector

    Files scanned: 21. 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

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Execution cost. Instruction body is 4029 tokens
    • 100Steps. 86 steps
    • 100Failures and branches. 11 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +4Description does not say when NOT to use the skill (false activations)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 415: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 86 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (4 of 4)
    • +3All 5 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This skill is a coherent paper-and-code analysis workflow that writes local analysis artifacts and an optional static reader, with no artifact-backed evidence of hidden exfiltration or destructive behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026