SKILLEMALL.ai

BD spec-driven-dev

在克隆的 Git 仓库中驱动完整的规格驱动开发生命周期(init→requirements→architecture→process_design→project_plan→coding→test→bugfix→code_review→release)。阶段门控、产物强制输出、多语言支持,内置 commit message 检查、代码门控与 LOGAF Checklist 评审,支持任意阶段 checkpoint 保存与 rollback 恢复,并实时发出结构化进度检查点。

ClawHub Agent Skills author: 胡实 v1.0.1 MIT-0 6 files body ≈ 4 638 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process D 47/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

TemplateSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
99
Quality 40%
66
Run on models
none yet
Process rating
D
47/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Exfiltration net-credential-use SKILL.md:242
    Credential used in a network call (verify the destination is the intended service) (destination host is a configured variable; quoted — discussed, not commanded)
    CLONE_URL="https://${GIT_USER}:${GIT_TOKEN}@${REMOTE_HOST}/$(echo "${git_remote}" | sed "s|https://${REMOTE_HOST}/||")"
    variable hostquoted

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")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 47/100

  • 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
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (python, node) that frontmatter does not declare
  • 70Execution cost. Instruction body is 4638 tokens
  • 100Steps. 147 steps
  • 100Consistency. Name and required fields are in place
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (5 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

  • +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 239: enough signal without eating the budget
  • +4Structure: 42 headings
  • +3Step-by-step instructions: 147 items
  • +4Has examples (27 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
This is a coherent Git workflow skill, but it needs Review because it stores a Git token on disk and can commit, tag, push, and roll back repository state with limited confirmation controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026