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BF napkin

Visual whiteboard collaboration for Copilot CLI. Creates an interactive whiteboard that opens in your browser — draw, sketch, add sticky notes, then share everything back with Copilot. Copilot sees your drawings and text, and responds with analysis, suggestions, and ideas.

github/awesome-copilot Agent Skills author: github MIT 2 files body ≈ 1 761 tokens Open the sourcegithub.com↗ analyzed 23 h ago

Visual whiteboard collaboration for Copilot CLI.

As a process F 50/100 · Will not run — References files that are not bundled: assets/step1-activate.svg, assets/step2-whiteboard.svg, assets/step3-draw.svg

IntegrationAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
Runs in: GitHub Copilot / VS Code Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
60
Run on models
none yet
Process rating
F
50/100
Will not run
References files that are not bundled: assets/step1-activate.svg, assets/step2-whiteboard.svg, assets/step3-draw.svg
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • 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-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: assets/step1-activate.svg
  • warning missing-ref reference to a missing file: assets/step2-whiteboard.svg
  • warning missing-ref reference to a missing file: assets/step3-draw.svg
  • warning missing-ref reference to a missing file: assets/step4-share.svg
  • warning missing-ref reference to a missing file: assets/step5-response.svg

Process rating: all ten parameters 50/100

Will not run. References files that are not bundled: assets/step1-activate.svg, assets/step2-whiteboard.svg, assets/step3-draw.svg
  • 0Tools and files. 5 referenced file(s) missing: assets/step1-activate.svg, assets/step2-whiteboard.svg, assets/step3-draw.svg
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 50Failures and branches. 0 branches, has a failure section
  • 85Steps. 40 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1761 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress

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 273: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 40 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.