SKILLEMALL.ai

AC think-plan

深度思考与规划 Skill。用于复杂任务的需求挖掘、方案设计和执行规划。 触发场景: 1. 用户说"帮我规划一下..."、"我想做一个..."、"分析一下这个方案" 2. 用户明确说"使用 think-plan"或"用思考规划 Skill" 3. 用户提出的任务需求不清晰、需要梳理 4. 用户需要多个可选方案对比 核心能力: - 批判性需求挖掘:客观指出用户想法的逻辑问题和认知偏差 - 自适应方案设计:根据复杂度决定单/多智能体架构 - 可落地执行规划:产出可直接执行的详细方案 工作流程:需求探讨 → 方案生成 → 执行实施

ClawHub Agent Skills author: caoyachao v1.0.0 MIT-0 5 files body ≈ 769 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
C
59/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
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: 5. 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 59/100

  • 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
  • 40Result and completion. Does not say what the result is
  • 100Tools and files. No external tools needed
  • 100Steps. 77 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 769 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

  • +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
  • +5Description quotes 5 example trigger phrases
  • +3Description length 268: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 77 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (2 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This is a planning skill with disclosed workspace plan-saving and optional execution coordination, but no evidence of hidden exfiltration, destructive behavior, or credential access.
LLM: benign (high) · VirusTotal: · 29 May 2026