SKILLEMALL.ai

BD changelog-generator-zh

Changelog生成 / 版本日志自动生成 / 发布说明自动撰写 / Release Notes generator。根据Git提交记录、功能列表或代码变更,自动生成结构清晰的版本更新日志。适用于技术负责人/研发经理整理发版改动、产品经理撰写版本说明、运维工程师记录系统升级历史。支持按功能分类(新增/修复/优化/破坏性变更),兼容Keep a Changelog格式标准。常见搜索触发词:版本更新怎么写、自动生成发布说明、Git提交转日志、版本记录怎么整理、发版前改动汇总、产品迭代文档模板、破坏性变更怎么标注。

ClawHub Agent Skills author: Olina1Ye v1.0.0 MIT-0 2 files body ≈ 141 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
D
43/100
Unfinished process
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 43/100

  • 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
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (git) that frontmatter does not declare
  • 100Steps. 5 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 141 tokens

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 258: enough signal without eating the budget
  • +4Structure: 4 headings
  • +3Step-by-step instructions: 5 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
The skills are mostly coherent and disclosed, but one review helper defaults to running a nested agent with full filesystem access and approval bypass, which deserves careful review before installation.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026