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BD UTF-8发布基础设施

为AI代理和开发者打造的UTF-8发布基础设施，自动处理跨平台编码问题，集成防卡顿策略和韧性保障，防止API token浪费，遵循'防止勤务干扰'原则。

ClawHub Agent Skills author: mrpulor-gh v2.0.1 MIT-0 7 files body ≈ 2 366 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype 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
79/100
safety, quality, tests
Safety 60%
91
Quality 40%
61
Run on models
none yet
Process rating
D
46/100
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

What is at stake

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

Secrets in code 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 files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

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 · 5

✓ No critical or high findings

Medium and low: 5
  • medium Secrets in code secret-github-token integration-test.js:12
    GitHub token (test fixture / example file; quoted — discussed, not commanded)
    const GITHUB_TOKEN = process.env.GITHUB_TOKEN || 'ghp_…53E';
    fixturequoted
  • low Exfiltration exfil-webhook-url cli.js:41
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    utf8…der test-discord https://discord.com/api/webhooks/... "测试消息"
    placeholder
  • low Exfiltration exfil-webhook-url integration-test.js:11
    Webhook / callback URL commonly used for exfiltration (verify the destination) (test fixture / example file; quoted — discussed, not commanded)
    const DISCORD_WEBHOOK = process.env.DISCORD_WEBHOOK_URL || 'https://discord.com/api/webhooks/1482573744688857109/tD4x…Uq6';
    fixturequoted
  • low Secrets in code secret-high-entropy-token integration-test.js:12
    High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file; quoted — discussed, not commanded)
    const GITHUB_TOKEN = process.env.GITHUB_TOKEN || 'ghp_…53E';
    fixturequoted
  • low Exfiltration exfil-webhook-url SKILL.md:189
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    'https://discord.com/api/webhooks/...',
    placeholder

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "read_when"

Process rating: all ten parameters 46/100

  • 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 (UTF-8发布基础设施) differs from the folder (utf8-encoder-skill)
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 64 steps
  • 100Execution cost. Instruction body is 2366 tokens
  • low 13 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)
  • +3Description length 76: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -222 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 54 headings
  • +3Step-by-step instructions: 64 items
  • +4Has examples (18 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.

External checks

ClawHub: suspicious
This skill is mostly a disclosed multi-platform publishing utility, but it ships real-looking embedded third-party credentials and has weak controls around posting and retaining content.
LLM: suspicious (high) · VirusTotal: malicious · 28 May 2026