BF revertwtf-catalog-research
Perform broader source-backed catalog enrichment for new EVM ecosystems, protocols, providers, standards, or deprecated/renamed/sunsetting coverage.
Perform broader source-backed catalog enrichment for new EVM ecosystems, protocols, providers, standards, or deprecated/renamed/sunsetting coverage.
As a process F 40/100 · Will not run — References files that are not bundled: scripts/enrich-new-ecosystem-shards.mjs
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: scripts/enrich-new-ecosystem-shards.mjs - note
edit-residuethe text marks something as outdated (lines 9, 10, 12): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 40/100
- 0Tools and files. 1 referenced file(s) missing: scripts/enrich-new-ecosystem-shards.mjs
- 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
- 20When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 21 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 661 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 148: enough signal without eating the budget
- +4Structure: 5 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.