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DF mplus-report-insight

(no description)

ClawHub Agent Skills author: lz0311-zhen v1.0.0 MIT-0 2 files body ≈ 668 tokens Open the sourceclawhub.ai↗ analyzed 8 d ago

你是否每次打开 Mplus 的 .out 文件都要用肉眼找 χ²、CFI、RMSEA？ 是否手动将一堆数字复制到 Excel 里制图，只为给导师看模型拟合好不好？ 这个助手能自动完成这些机械工作，并为你生成符合 APA 7 标准的完整分析报告。 上传 Mplus 的 .out 文本文件，自动执行：

As a process F 33/100 · No process to follow — References files that are not bundled: scripts/main.py, scripts/validate.py, scripts/utils.sh

ProcedureData and analyticstype 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
D
60/100
safety, quality, tests
Safety 60%
100
Quality 40%
0
Run on models
none yet
Process rating
F
33/100
No process to follow
References files that are not bundled: scripts/main.py, scripts/validate.py, scripts/utils.sh
Tools and files w 18
0
Result and completion w 14
0
When it triggers w 12
0
the three weakest of ten parameters · all ten

How to improve

  1. Add a description to the frontmatter: without it the skill never triggers.
  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

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger
  • warning missing-ref reference to a missing file: scripts/main.py
  • warning missing-ref reference to a missing file: scripts/validate.py
  • warning missing-ref reference to a missing file: scripts/utils.sh
  • warning missing-ref reference to a missing file: references/background.md
  • warning missing-ref reference to a missing file: references/operating-rules.md
  • warning missing-ref reference to a missing file: references/examples.md
  • warning missing-ref reference to a missing file: assets/schema.json

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: scripts/main.py, scripts/validate.py, scripts/utils.sh
  • 0Tools and files. 7 referenced file(s) missing: scripts/main.py, scripts/validate.py, scripts/utils.sh
  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 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
  • 100Steps. 33 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 668 tokens
  • 100Running it twice. No mutating operations

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 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -214 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 33 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.

External checks

ClawHub: clean
This is a local Mplus report-generation skill with no bundled executable code, persistence, credential access, or hidden data movement evident in the artifact.
LLM: benign (high) · 16 Sept 2026