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AB code-archaeology

Analyze legacy codebases to extract business rules, technical specifications, and migration requirements. Use when analyzing PHP, Java, Python, or other legacy systems for modernization planning.

ClawHub Agent Skills author: roboe v2.5.0 MIT-0 10 files · 3 scripts body ≈ 1 726 tokens Open the sourceclawhub.ai↗ analyzed 14 d ago

Analyze legacy codebases to extract business rules, technical specifications, and migration requirements.

As a process B 70/100 · Nearly there — weak spots: when it triggers, failures and branches, 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%
100
Quality 40%
87
Run on models
none yet
Process rating
B
70/100
Nearly there
Failures and branches w 10
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 · 0

    ✓ No critical or high findings

    Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 6, 8, 73, 77, 91, 97): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 70/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 47 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Result and completion. Output format and completion criterion are stated
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1726 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 195: enough signal without eating the budget
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 47 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)

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

    External checks

    ClawHub: suspicious
    The skill is mostly aligned with legacy-code analysis, but one included utility can write outside its intended workspace if given a crafted project name.
    LLM: suspicious (medium) · VirusTotal: · 15 Sept 2026