SKILLEMALL.ai
GitHub ↗ RU Sign in

BF internalize_me

Analyze an open-source project against an AI/Agent-engineer job-market competency framework so the user can learn from real code. Use when the user asks to "analyze this project", "帮我分析这个开源项目", "看看这个项目练什么能力", "internalize this project", or wants to turn a repo into a learning plan aligned with AI Agent / LLM engineering job requirements.

ClawHub Agent Skills author: zhaoyta v1.0.1 MIT-0 2 files body ≈ 2 692 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Analyze an open-source project against an AI/Agent-engineer job-market competency framework so the user can learn from real code.

As a process F 39/100 · Will not run — References files that are not bundled: 02-xxx.md, 03-xxx.md, tasks.md

AnalyzerAI and agentstype 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
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
F
39/100
Will not run
References files that are not bundled: 02-xxx.md, 03-xxx.md, tasks.md
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 · 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 name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning missing-ref reference to a missing file: 02-xxx.md
  • warning missing-ref reference to a missing file: 03-xxx.md
  • warning missing-ref reference to a missing file: tasks.md

Process rating: all ten parameters 39/100

Will not run. References files that are not bundled: 02-xxx.md, 03-xxx.md, tasks.md
  • 0Tools and files. 3 referenced file(s) missing: 02-xxx.md, 03-xxx.md, tasks.md
  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (internalize_me) differs from the folder (internalize-me)
  • 50Failures and branches. 0 branches, has a failure section
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 91 steps
  • 100Execution cost. Instruction body is 2692 tokens
  • low The skill ranks results itself: that belongs to the system behind the tool, not the model

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

  • +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
  • +5Description quotes 4 example trigger phrases
  • +3Description length 339: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 91 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: clean
This appears to be a documentation-focused skill whose file changes are aligned with building and reviewing repository docs.
LLM: benign (medium) · VirusTotal: · 9 Jul 2026