AC decision-clarity
Improve decision quality by clarifying the real problem, exposing hidden assumptions, reasoning from fundamental facts, reducing unnecessary complexity, and ending with a cleaner recommendation or next step. Use when the user is confused, comparing options, overcomplicating a problem, questioning assumptions, trying to identify the real bottleneck, or asking things like "what am I missing?", "does this really have to be this way?", "what should I remove?", "what is the simplest explanation that still fits?", or "help me think this through".
As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
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: 15. 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 61/100
- 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. 2 mutating operations with no state check
- 40Consistency. Frontmatter name (decision-clarity) differs from the folder (decision-clarity-skill)
- 55Failures and branches. 1 branches
- 100Tools and files. No external tools needed
- 100Steps. 124 steps
- 100When it triggers. States when to use and when not to
- 100Execution cost. Instruction body is 1926 tokens
- low 10 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
- +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
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 546: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 124 items
- +4Reference files are cited in the instructions (8 of 8)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.