AC boyue
Decision and complexity governance for AI-assisted software development / 面向 AI 编程的软件项目决策与复杂度治理。Use when planning products or features, evaluating scope expansion, making hard-to-reverse decisions, validating uncertain AI capabilities, deciding whether experimental code belongs in production, or reviewing mature systems for simplification and retirement. Do not slow down low-risk reversible edits.
Decision and complexity governance for AI-assisted software development / 面向 AI 编程的软件项目决策与复杂度治理。Use when planning products or features, evaluating scope…
As a process C 59/100 · Has gaps — 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: 14. 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 59/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 17 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. No external tools needed
- 100Steps. 75 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1717 tokens
- low 12 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)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +2Single-language instructions
- +3Description length 400: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 75 items
- +4Reference files are cited in the instructions (5 of 5)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.