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AC cjpkg

Helps users discover, when they ask questions like "how do I do X", "find a packages for Cangjie", "is there a X package for Cangjie...", or express interest in extending capabilities. This package or third party component should be used when the user is looking for functionality that might exist as an cangjie package.

ClawHub Agent Skills author: l3gi0nXXXX v1.0.0 MIT-0 3 files body ≈ 2 242 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureInfrastructuretype 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
A
95/100
safety, quality, tests
Safety 60%
99
Quality 40%
88
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    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-shell-rc SKILL.md:110
      Writes to a shell startup file (detector / deny-list definition)
      * If you run on macOS/Linux → `echo "source SDK_PATH/envsetup.sh" >> .zshrc & source .zshrc`
      detector

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

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 58/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 11 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 7 branches
    • 100Steps. 41 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2242 tokens
    • 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +3Description length 321: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 41 items
    • +4Has examples (6 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    This Cangjie package helper is mostly related to package management, but it gives agents broad permission to change projects and persistent shell settings without enough scoping or rollback guidance.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026