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BD qimen-dunjia

奇门遁甲排盘分析器，基于洛书九宫四层盘面体系（天盘九星、地盘三奇六仪、人盘八门、神盘八神）， 支持时家奇门排盘，用于择时决策和事项预测。当用户提及「奇门遁甲」「奇门」「遁甲」「择时」 「奇门排盘」「奇门预测」时触发。排盘为确定性计算 + LLM 综合解读，无外部 API 依赖。 不适用于：梅花易数、六爻易经、风水分析、八字命理、塔罗占卜等其他领域 → 建议使用 fortune-hub 路由。

ClawHub Agent Skills author: eamanc v1.0.0 MIT-0 4 files body ≈ 1 180 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

IntegrationInfrastructureAI 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
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "clawhub-slug"
  • note frontmatter-key unknown frontmatter key "clawhub-owner"
  • note frontmatter-key unknown frontmatter key "homepage"

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 (qimen-dunjia) differs from the folder (qimen-dunjia-oracle)
  • 100Tools and files. No external tools needed
  • 100Steps. 22 steps
  • 100Execution cost. Instruction body is 1180 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)
  • +3Output format is not stated: the model decides each time
  • -212 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 197: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +1License stated

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

External checks

ClawHub: clean
This is a local markdown-only Qimen Dunjia divination skill with disclosed optional preference memory and no code execution, network use, or credential access.
LLM: benign (high) · VirusTotal: · 29 May 2026