SKILLEMALL.ai

AC task-prism

任务拆解与技能画像专家。将模糊复杂的业务需求系统化拆解为高可执行性的工作模块、技能画像及落地流程。当用户需要:任务拆解、需求澄清、项目规划、WBS工作分解、技能画像梳理、岗位职能匹配、流程动线设计、交付成果界定、成本预算规划、风险管理、变更管理、沟通管理、可行性评估时触发。适用于任何行业的项目管理、组织效能提升、方案策划场景。支持四种工作模式:快速模式、完整模式、敏捷模式、跨国/跨文化模式。即使只说'帮我拆解任务'、'做个项目计划'、'任务怎么分工'也应触发。

ClawHub Agent Skills author: qomob v4.1.0 MIT-0 5 files body ≈ 2 669 tokens Open the sourceclawhub.ai analyzed 30 h ago

任务拆解与技能画像专家。将模糊复杂的业务需求系统化拆解为高可执行性的工作模块、技能画像及落地流程。当用户需要:任务拆解、需求澄清、项目规划、WBS工作分解、技能画像梳理、岗位职能匹配、流程动线设计、交付成果界定、成本预算规划、风险管理、变更管理、沟通管理、可行性评估时触发。适用于任何行业的项目管理、组织效能提升、方案…

As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

ProcedureLearningData and analyticsOperations and projectstype 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
C
62/100
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

The same skill appears in 1 more place: ClawHub

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 62/100

  • 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
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. No external tools needed
  • 100Steps. 60 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2669 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 232: enough signal without eating the budget
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 60 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

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

External checks

ClawHub: clean
This is a project-planning prompt skill with no executable code or sensitive system access, though its README includes a remote image and its activation wording is broad.
LLM: benign (high) · VirusTotal: · 15 Jun 2026