SKILLEMALL.ai

AB repo-analysis

Read, explain, and evaluate a software repository or GitHub project in an engineering-oriented way. Use when the user asks to read a repo, understand a codebase, analyze architecture, evaluate whether a project is worth following or adopting, prepare onboarding notes, or summarize stack, module boundaries, risks, and entry points. Supports three output modes: 速读版, 架构版, and 接手评审版. Also supports a lightweight GitHub health layer for public repositories when the user asks whether a project is worth following, adopting, or referencing. Triggers include requests like 读一下这个项目, 看看这个 GitHub 仓库, 分析一下 repo, 这个项目怎么样, 帮我快速理解代码结构, 给我一个架构分析, or 给我一个接手评审.

ClawHub Agent Skills author: JY v0.4.0 MIT-0 6 files body ≈ 3 193 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 75/100 · Nearly there — weak spots: inputs and preconditions

AnalyzerGitHubSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
B
75/100
Nearly there
Inputs and preconditions w 11
0
Result and completion w 14
60
When it triggers w 12
70
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 · 0

    ✓ No critical or high findings

    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 75/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 6 branches
    • 85Steps. 248 steps, 2 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3193 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low 13 top-level sections: this looks like several domains in one skill

    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 648: enough signal without eating the budget
    • +4Structure: 50 headings
    • +3Step-by-step instructions: 248 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (4 of 4)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This is an instruction-only repository analysis skill whose disclosed file-reading behavior fits its purpose.
    LLM: benign (high) · VirusTotal: · 29 May 2026