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BC rd-initiation-review-zhcn

研发项目立项预审与提案审查，用于立项通过/否决决策、公开新颖性边界审查、创新点评估及有据可查的项目评级。当用户要求进行项目立项预审、立项评审、提案审查、研发项目评估、提案包审查、新颖性预查、创新点评审、项目评级，或希望围绕具体项目、提案或研究包材料集开展正式评审时使用——即使用户仅提供提案而未明确说明「评审」也适用。

ClawHub Claude Code author: yuanzhian-patsnap v1.0.1 MIT-0 18 files body ≈ 1 675 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

研发项目立项预审与提案审查，用于立项通过/否决决策、公开新颖性边界审查、创新点评估及有据可查的项目评级。当用户要求进行项目立项预审、立项评审、提案审查、研发项目评估、提案包审查、新颖性预查、创新点评审、项目评级，或希望围绕具体项目、提案或研究包材料集开展正式评审时使用——即使用户仅提供提案而未明确说明「评审」也适用。

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentsData 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
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
C
53/100
Has gaps
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: 18. 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 "copyright"
  • note frontmatter-key unknown frontmatter key "provider"
  • note frontmatter-key unknown frontmatter key "deliverable-default"
  • note frontmatter-key unknown frontmatter key "fallback-policy"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 165 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1675 tokens
  • 100Running it twice. No mutating operations
  • low 12 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)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 159: enough signal without eating the budget
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 165 items
  • +4Reference files are cited in the instructions (7 of 7)

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

External checks

ClawHub: suspicious
This is a coherent R&D proposal review skill, but it needs Review because it can activate on a merely provided proposal and use external searches with potentially sensitive project content.
LLM: suspicious (high) · 13 Aug 2026