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AI开发助手项目接入技能。功能:(1)内置 deploy.cmd/deploy.ps1/deploy.sh,支持双击、右键"发送到"、命令行、以及 -Vendor 把技能包内嵌进项目供团队分发,一键把参考资料包部署到目标项目并自动落地各工具规则 (2)配置Trae/CodeBuddy/Claude Code/opencode四款工具规则 (3)生成需求/设计/测试/审查标准模板 (4)10个快捷指令Workflow覆盖全流程 (5)1WEEK/3DAY/1DAY三级任务复杂度分级。当用户需要在项目中接入AI辅助开发流程、把技能包/参考资料包部署或拷贝到工程目录、让团队其他成员也能直接用上AI开发助手、配置AI工具规则、生成标准化模板时使用此技能。

ClawHub Agent Skills author: 麟览 v1.0.2 MIT-0 43 files · 4 scripts body ≈ 2 093 tokens Open the sourceclawhub.ai analyzed 13 h ago

AI开发助手项目接入技能。功能:(1)内置 deploy.cmd/deploy.ps1/deploy.sh,支持双击、右键"发送到"、命令行、以及 -Vendor 把技能包内嵌进项目供团队分发,一键把参考资料包部署到目标项目并自动落地各工具规则 (2)配置Trae/CodeBuddy/Claude…

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
D
45/100
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: 43. 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")

Process rating: all ten parameters 45/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 19 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 16 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2093 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

  • +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
  • +1No license
  • +2Single-language instructions
  • +3Description length 327: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 16 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
This is a disclosed project setup helper, but it should go to Review because one Windows vendoring option can write outside the selected project and the docs encourage automatic deployment from broad prompts.
LLM: suspicious (high) · 13 Sept 2026