SKILLEMALL.ai

AC claw-team-builder

Agent Team 规划与配置工具。通过多轮交互澄清需求,自动创建 Agent 配置、工作空间、Bootstrap 文件。 触发场景: - 用户说"创建新 Agent" / "新建 bot" / "配置多个 bot" - 用户说"规划 agent team" / "我需要几个不同的 agent" - 用户说"添加一个 agent" / "帮我建一个新 agent" - 用户提到需要不同场景使用不同的 AI 角色 功能: 1. 需求澄清 - 引导用户描述使用场景和 Agent 定位 2. 配置读取 - 自动读取现有 openclaw.json,分析已有配置 3. 方案设计 - 推荐 Agent 配置方案,检测冲突 4. 自动创建 - 创建目录、文件、更新配置 5. 配置验证 - 确保配置正确可用

ClawHub Agent Skills author: 8421bit v1.0.0 5 files body ≈ 471 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
C
51/100
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: 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 51/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 28 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 471 tokens

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 7 example trigger phrases
  • +3Description length 354: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (2 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: suspicious
The skill does what it says by creating OpenClaw agents, but it can persistently edit global OpenClaw configuration and run mutating repair commands without enough built-in safeguards.
LLM: suspicious (high) · VirusTotal: · 29 May 2026