SKILLEMALL.ai

BD github-acr-release

全周期项目发布管控:覆盖版本创建→开发→预发布→发布→验证→运维→下版本规划的13步标准流程。交互式配置、版本一致性检测、可持续性评分、热更新。适用于任何语言、任何 Docker 部署项目。触发词:新建发布流程、发布、检查、热更新、下个版本。

ClawHub Agent Skills author: dongjie-oss v2.1.0 MIT-0 3 files body ≈ 2 204 tokens Open the sourceclawhub.ai analyzed 13 h ago

全周期项目发布管控:覆盖版本创建→开发→预发布→发布→验证→运维→下版本规划的13步标准流程。交互式配置、版本一致性检测、可持续性评分、热更新。适用于任何语言、任何 Docker 部署项目。触发词:新建发布流程、发布、检查、热更新、下个版本。

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

ProcedureGitHubDockerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
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: 3. 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. 6 mutating operations with no state check
  • 60Tools and files. Uses tools (git, python, node) that frontmatter does not declare
  • 100Steps. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2204 tokens
  • low 12 top-level sections: this looks like several domains in one skill

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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -2localhost URLs: will not work for another user
  • -240 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 121: enough signal without eating the budget
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: clean
This is a disclosed release-management skill that can perform powerful git, Docker, ACR, and SSH deployment steps, but its behavior matches its stated purpose and includes user-confirmation requirements.
LLM: benign (high) · VirusTotal: · 13 Jun 2026