SKILLEMALL.ai

AB safe-refactor

Execute a behavior-preserving refactor with a proof of preservation — establishes a safety net first (existing tests or new characterization tests over every touched path), locks a baseline green run, then moves in small always-green steps where each step is one mechanical transformation, and treats any needed assertion change as a smuggled behavior change to surface, not fix. Use this skill whenever the user says "refactor this", "clean this up without changing behavior", "extract this into", "restructure this module", "rename this across the codebase", "inline this", "split this function/class", or "/safe-refactor" — even if they don't explicitly say "refactoring skill". Do not use for choosing WHAT to refactor (use improve-codebase-architecture) or for changes that are supposed to alter behavior (use task-executor).

ClawHub Agent Skills author: Dennis Rongo v1.0.0 MIT-0 2 files body ≈ 2 030 tokens Open the sourceclawhub.ai analyzed 35 h ago

Execute a behavior-preserving refactor with a proof of preservation — establishes a safety net first (existing tests or new characterization tests over every…

As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
B
65/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
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: 2. 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 65/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 10 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 26 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2030 tokens
    • 100Progress reporting. Reports progress

    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

    • +3Description length 830: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -212 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 9 example trigger phrases
    • +4Description says when NOT to use the skill
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (0 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    This skill gives cautious instructions for behavior-preserving code refactors and does not add hidden execution, data access, persistence, or credential handling.
    LLM: benign (high) · VirusTotal: · 16 Aug 2026