SKILLEMALL.ai
GitHub ↗ RU Sign in

BD skill-creator

Create, update, validate, and evaluate Wisp skills. Use when authoring a project-local or installable skill, refining its trigger description, adding deterministic scripts or Python/R runtime sidecars, or testing whether another Agent can follow the workflow.

xuzhougeng/wisp-science Agent Skills author: xuzhougeng AGPL-3.0 3 files · 2 scripts body ≈ 1 179 tokens Open the sourcegithub.com↗ analyzed 7 d ago

Create, update, validate, and evaluate Wisp skills.

As a process D 38/100 · Unfinished process — References files that are not bundled: scripts/runtime.py, scripts/runtime.r

AnalyzerSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
91/100
safety, quality, tests
Safety 60%
99
Quality 40%
78
Run on models
none yet
Process rating
D
38/100
Unfinished process
References files that are not bundled: scripts/runtime.py, scripts/runtime.r
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. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-eval-dynamic SKILL.md:40
    Dynamic code execution from decoded/untrusted input (quoted — discussed, not commanded)
    instruction for each file: `exec(compile(...))` through `python`, or
    quoted

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/runtime.py
  • warning missing-ref reference to a missing file: scripts/runtime.r

Process rating: all ten parameters 38/100

Will not run. References files that are not bundled: scripts/runtime.py, scripts/runtime.r
  • 0Tools and files. 2 referenced file(s) missing: scripts/runtime.py, scripts/runtime.r
  • 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
  • 30Running it twice. 5 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 100Steps. 22 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1179 tokens
  • low The response is described with custom markup (6 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 259: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (2 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.