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BD gitea-routine-report

获取 Gitea 各仓库提交记录，调用 AI 生成进度报告，并发送 HTML 邮件给仓库管理员

ClawHub Agent Skills author: myd2002 v1.2.0 MIT-0 11 files · 1 script body ≈ 1 108 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
95
Quality 40%
64
Run on models
none yet
Process rating
D
39/100
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
This is a copy of a skill from another catalog; the rating counts the canonical one: gitea-routine-report (ClawHub)

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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
  • medium Broad scope meta-requests-env-secret SKILL.md:1
    Skill asks the runtime to inject credential env vars into its sandbox: GITEA_TOKEN — verify each one is needed for the stated purpose
    required_environment_variables: GITEA_TOKEN

Files scanned: 11. 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 "required_environment_variables"
  • note frontmatter-key unknown frontmatter key "primary_credential"
  • note frontmatter-key unknown frontmatter key "credentials"
  • note frontmatter-key unknown frontmatter key "environment_file"

Process rating: all ten parameters 39/100

  • 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. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (gitea-routine-report) differs from the folder (gitea-commit-report-skills)
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 35 steps
  • 100Execution cost. Instruction body is 1108 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)
  • +3Description length 47: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -33 of 4 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 35 items
  • +4Has examples (9 code blocks)
  • +1License stated

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

External checks

ClawHub: suspicious
This Gitea reporting skill is mostly coherent, but it can gather activity data across all visible repositories and email it to derived recipients without a required confirmation step.
LLM: suspicious (high) · VirusTotal: · 29 May 2026