AC xiaoyaoclaw-agent-orchestrator
OpenClaw multi-agent daily collaboration orchestrator: split a task into subtasks, dispatch to resident agents via sessions_send, track progress via sessions_list/sessions_history, aggregate results with source attribution, and retry failures (default max 3). Reads openclaw.json for agents.list and agentToAgent.allow (bidirectional whitelist); three-tier trigger (explicit dispatch / suggest+ask for fuzzy big tasks / silent otherwise). Use when user asks to orchestrate/coordinate multiple agents, dispatch parallel work, delegate to a named agent, or aggregate results from several agents (orchestrate/parallel/delegate/让 XX 做/编排/并行/ 分给/汇总). 中文：OpenClaw 多 Agent 日常协作编排器——任务拆解、跨 agent 分发（强制 sessions_send）、进度追踪、结果聚合、失败重试（默认最多 3 次）。 三档触发：用户点名或含编排动词直接执行；模糊大任务建议并行并询问用户； 其余情况保持沉默。直接读 openclaw.json（agents.list + agentToAgent.allow 双向白名单）获取 agent 名单与授权。适用于多 agent 家庭协作、并行调研、批量巡检、发布前多视角审查、团队日报汇总等场景。
OpenClaw multi-agent daily collaboration orchestrator: split a task into subtasks, dispatch to resident agents via sessionssend, track progress via…
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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 · 2
✓ No critical or high findings
Medium and low: 2
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low Secrets in code
secret-high-entropy-tokenREADME.en.md:15High-entropy token-like string (may be an id, hash or a credential)[[ that frontmatter does not declare
- 100Steps. 36 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1109 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 897: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +4Structure: 17 headings
- +3Step-by-step instructions: 36 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (3 of 4)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.