AC propaymun-information-architecture
Shape, review, and validate end-to-end product information architecture, product/UX sitemaps, and stateful user flows when users need clearer structure, labels, relationships, access, findability, destinations, or task paths. Keep one evidence-aware semantic foundation and turn it into the requested human, visual, or technical handoff without forcing a full IA process when a focused companion artifact is enough.
Shape, review, and validate end-to-end product information architecture, product/UX sitemaps, and stateful user flows when users need clearer structure…
As a process C 63/100 · 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: 23. 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 63/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 8 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (propaymun-information-architecture) differs from the folder (propaymun-information-architecture-skill)
- 50When it triggers. No condition that starts the skill
- 70Execution cost. Instruction body is 4592 tokens
- 100Tools and files. No external tools needed
- 100Steps. 50 steps
- 100Failures and branches. 1 branches, has a failure section
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- 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
- +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
- +2Single-language instructions
- +3Description length 415: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 50 items
- +4Has examples (0 code blocks)
- +4Reference files are cited in the instructions (12 of 12)
- +3All 4 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.