AC skill-retrieval-gate
Decide whether to run `memory_search` before following another skill or workflow, so the agent can reduce token usage without forcing retrieval on every task. Use when a task may depend on local knowledge, project history, prior decisions, user preferences, or existing notes, and you need a lightweight rule for when to retrieve, how to query, how much context to load, and when to fall back. Typical triggers include requests like: continue previous work, use project memory first, check what we already documented, base this on existing notes, or decide whether retrieval is worth it before following the skill.
Decide whether to run memorysearch before following another skill or workflow, so the agent can reduce token usage without forcing retrieval on every task.
As a process C 63/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, progress reporting
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: 7. 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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Inputs and preconditions. Does not say what the process needs to start
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 31 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 605 tokens
- 100Running it twice. No mutating operations
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)
- +1No license
- +2Single-language instructions
- +3Description length 614: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 31 items
- +3Output format is stated explicitly
- +4Has examples (0 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.