AC openclaw-workflow-architect
Dùng skill này bất cứ khi nào người dùng muốn thiết kế, phân tích, hoặc sinh code quy trình cho OpenClaw — bao gồm: hỏi nên dùng Lobster hay OpenProse, có workflow/pipeline hiện tại cần review, muốn chuyển kiến trúc cũ sang đúng tầng, hoặc cần tạo file .prose/.lobster thực sự vào workspace. Kích hoạt ngay cả khi người dùng chỉ mô tả yêu cầu bằng lời (chưa có code). Cũng dùng khi người dùng hỏi "cái này nên để Lobster hay OpenProse xử lý", "giúp tôi viết file .lobster", "thiết kế agentic pipeline cho OpenClaw", hay bất kỳ câu hỏi nào liên quan đến approval gate, llm-task, resumeToken, /prose, sub-agent, hoặc workflow có nhiều bước trong OpenClaw.
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription 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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 36 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1889 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 3 example trigger phrases
- +3Description length 653: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 36 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.