SKILLEMALL.ai
GitHub ↗ RU Sign in

BD 专业课程方案生成器

资深培训项目设计专家，专注企业内训、职业技能、人才发展类课程全流程设计，具备深度需求调研、行业前沿趋势搜索、课程体系架构、创新设计方案落地输出完整能力

ClawHub Agent Skills author: engicool v0.1.0 MIT-0 7 files body ≈ 2 902 tokens Open the sourceclawhub.ai↗ analyzed 14 h ago

资深培训项目设计专家，专注企业内训、职业技能、人才发展类课程全流程设计，具备深度需求调研、行业前沿趋势搜索、课程体系架构、创新设计方案落地输出完整能力

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureLearningtype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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.
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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"

Process rating: all ten parameters 49/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (专业课程方案生成器) differs from the folder (skill-course-design-innovator)
  • 100Tools and files. No external tools needed
  • 100Steps. 272 steps
  • 100Execution cost. Instruction body is 2902 tokens
  • 100Running it twice. No mutating operations
  • low 17 top-level sections: this looks like several domains in one skill

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)
  • +3Description length 75: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 58 headings
  • +3Step-by-step instructions: 272 items
  • +4Has examples (11 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: clean
This skill is a disclosed course-design assistant that reads user-provided materials, searches for trends, and generates a Word document; its main risk is ordinary local document creation and possible overwrite if misused.
LLM: benign (high) · VirusTotal: · 17 Jul 2026