AB simplify-codebase
Simplification audit or authorized codebase simplification whose stated objective is to remove accidental complexity. Use for evidence-backed deletion or consolidation of dead code, duplicate state, redundant APIs or layers, ownerless abstractions, obsolete compatibility or design records, and over-engineering in any language; also use for 代码简化 or 熵回收. Do not use for general code review, onboarding, style-only refactoring, or performance tuning.
The skill audits codebases to strip accidental complexity: dead code, duplicate state, redundant abstractions. Promises to identify and remove architectural clutter.
Files check out clean: 8 documents, no syntax errors, 1600 tokens of instructions. Scores are solid—quality 93, safety 100. Zero critical findings, none at medium level either. In practice this means the prompt is well-formed and won't trigger model conflicts. Runs on all major platforms from Claude to DeepSeek.
Install if your project has genuinely accumulated complexity and needs systematic cleanup. Skip it for routine refactoring or style-only fixes.
Simplification audit or authorized codebase simplification whose stated objective is to remove accidental complexity.
As a process B 72/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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: 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 72/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 60Failures and branches. 2 branches
- 100Tools and files. No external tools needed
- 100Steps. 8 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1600 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
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 449: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 8 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.