SKILLEMALL.ai

BC famou-artifact-generator

交互式引导用户完成 FaMou 进化任务的完整流程:先通过结构化澄清循环产出 `problem.md`,再实现并验证 FaMou 实验的三个输入物料(`init.py`、`evaluator.py`、`prompt.md`)。当用户提到以下任意情形时触发:定义/澄清/创建 FaMou 任务、帮我写 problem.md、我想建一个进化任务、帮我准备 FaMou 实验物料、生成 init.py 或 evaluator.py、优化/ML/搜索问题需要进化求解。即使用户只说"帮我做个 FaMou 任务"或提供粗略想法,也应触发此技能并从澄清阶段开始。

ClawHub Agent Skills author: FaMou v1.0.1 MIT-0 2 files body ≈ 860 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
C
53/100
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: 2. 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 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 47 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 860 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)
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 275: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 47 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: clean
This is a disclosed FaMou task-generation helper that reads local project context, writes named task files, and validates them without hidden install hooks or credential behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026