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BF tekan-skill

生成、编辑、协作。一个工具包接入所有主流 AI 模型。只需描述你的创意，即可生成视频、图片和数字人——零手动操作。当用户提到以下任何内容时使用此技能：特看视频、生成视频或图片、数字人、口型同步、文字转语音、TTS、声音克隆、去除背景、商品模特图、电商图、商品详情图、商品主图、虚拟穿搭、图片转视频、文字转视频、AI 图片编辑，或任何创意内容生成工作流——即使他们没有明确说出具体工具名或'特看视频'。

ClawHub Agent Skills author: tekancn v1.0.0 MIT-0 33 files body ≈ 5 353 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 31/100 · Will not run — References files that are not bundled: <LOGIN_URL>, <VIDEO_URL>, <IMAGE_URL>

ProcedureInfrastructuretype 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
78/100
safety, quality, tests
Safety 60%
93
Quality 40%
56
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: <LOGIN_URL>, <VIDEO_URL>, <IMAGE_URL>
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.

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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. The text references files that are not there: add them or drop the references.
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 · 3

✓ No critical or high findings

Medium and low: 3
  • medium Broad scope meta-agent-memory-dump references/user.md
    Agent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokens
    references/user.md
  • low Secrets in code secret-high-entropy-token references/avatar4.md:41
    High-entropy token-like string (may be an id, hash or a credential)
    --voice LaaH…tW6
  • low Secrets in code secret-password-literal scripts/auth.py:46
    Hard-coded password / key literal (may be an example)
    api_key = api_keys[0] if api_keys else ""

Files scanned: 33. 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")
  • warning body-long SKILL.md body ≈ 5353 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: <LOGIN_URL>
  • warning missing-ref reference to a missing file: <VIDEO_URL>
  • warning missing-ref reference to a missing file: <IMAGE_URL>
  • warning missing-ref reference to a missing file: 完整URL

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: <LOGIN_URL>, <VIDEO_URL>, <IMAGE_URL>
  • 0Tools and files. 4 referenced file(s) missing: <LOGIN_URL>, <VIDEO_URL>, <IMAGE_URL>
  • 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. 14 mutating operations with no state check
  • 70Execution cost. Instruction body is 5353 tokens
  • 100Steps. 73 steps
  • 100Consistency. Name and required fields are in place
  • low 13 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (10 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
  • -213 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 200: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 73 items
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (13 of 13)
  • +3All 11 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.

External checks

ClawHub: suspicious
This appears to be a real Tekan media-generation skill, but it needs review because it stores account credentials and can automatically upload personal media or spend credits with weak confirmation.
LLM: suspicious (high) · VirusTotal: · 29 May 2026