AC propaymun-information-architecture
Guide information architecture (IA) design and review when users ask for IA or need to organize, label, relate, or find product information. Optional local Python helpers validate IA JSON and export HTML or builder specifications on request. Do not activate for general product strategy, UI design, database/API architecture, standalone access-policy questions, sitemap-only, or user-flow-only requests.
Guide information architecture (IA) design and review when users ask for IA or need to organize, label, relate, or find product information.
As a process C 57/100 · 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: 18. 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 57/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Execution cost. Instruction body is 4935 tokens
- 85Steps. 92 steps, 1 vague phrases
- 100Failures and branches. 2 branches, has a failure section
- 100Running it twice. Mutating operations check current state
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 11 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
- -33 of 3 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 403: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 92 items
- +4Reference files are cited in the instructions (10 of 10)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.