BF craw-figma
Full bidirectional Figma integration — read files via REST API, create/modify/delete layers via local WebSocket connector + Figma plugin. Audit accessibility, extract design tokens, export assets. Write operations appear in real time on Figma Desktop.
Full bidirectional Figma integration — read files via REST API, create/modify/delete layers via local WebSocket connector + Figma plugin.
As a process F 46/100 · Will not run — References files that are not bundled: scripts/style-dictionary/build/variables.css, scripts/style-dictionary/build/figma-tokens.json
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: 9. 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/style-dictionary/build/variables.css - warning
missing-refreference to a missing file: scripts/style-dictionary/build/figma-tokens.json - note
edit-residuethe text marks something as outdated (lines 177, 178): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 46/100
- 0Tools and files. 2 referenced file(s) missing: scripts/style-dictionary/build/variables.css, scripts/style-dictionary/build/figma-tokens.json
- 0Result and completion. Does not say what the result is
- 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
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 22 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2239 tokens
- 100Running it twice. Mutating operations check current state
- low The response is described with custom markup (11 tags): a typed call is more reliable
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
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +3Description length 251: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.