SKILLEMALL.ai

BC multica-sdd-workflow

SDD + Multica 多智能体开发工作流。当用户提到"新建任务"、"发布给 multica"、"创建小队"、 "分配 issue"、"开始新功能"、"组建小队执行"、"按 SDD 流程"、"新增功能"、"功能更新"时触发。 覆盖从 SDD 规范文档编写、multica 小队创建、Issue 发布执行,到完成后记录归档的完整流程。

ClawHub Agent Skills author: denghuayuan v1.0.0 MIT-0 4 files body ≈ 1 585 tokens Open the sourceclawhub.ai analyzed 3 d ago

SDD + Multica 多智能体开发工作流。当用户提到"新建任务"、"发布给 multica"、"创建小队"、 "分配 issue"、"开始新功能"、"组建小队执行"、"按 SDD 流程"、"新增功能"、"功能更新"时触发。 覆盖从 SDD 规范文档编写、multica 小队创建、Issue…

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
C
56/100
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: 4. 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")
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 56/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 9 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1585 tokens
  • low The response is described with custom markup (3 tags): a typed call is more reliable

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
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 168: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (14 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
The skill is a coherent Multica SDD workflow, but its broad trigger phrases can activate state-changing multi-agent and project-management actions without an explicit confirmation gate.
LLM: suspicious (medium) · VirusTotal: · 7 Jun 2026