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、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'。
As a process F 28/100 · Will not run — References files that are not bundled: 完整URL, <LOGIN_URL>, ...
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
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.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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-dumpreferences/user.mdAgent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokensreferences/user.md
-
low Secrets in code
secret-high-entropy-tokenreferences/avatar4.md:41High-entropy token-like string (may be an id, hash or a credential)--voice LaaH…tW6
-
low Secrets in code
secret-password-literalscripts/auth.py:45Hard-coded password / key literal (may be an example)api_key = api_keys[0] if api_keys else ""
Files scanned: 32. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: 完整URL - warning
missing-refreference to a missing file: <LOGIN_URL> - warning
missing-refreference to a missing file: ... - warning
missing-refreference to a missing file: <VIDEO_URL> - warning
missing-refreference to a missing file: <IMAGE_URL>
Process rating: all ten parameters 28/100
- 0Tools and files. 5 referenced file(s) missing: 完整URL, <LOGIN_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
- 40Consistency. Frontmatter name (tekan-skill) differs from the folder (tekan)
- 100Steps. 72 steps
- 100Execution cost. Instruction body is 3467 tokens
- low 13 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (5 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
- -31 of 11 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 180: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 72 items
- +4Has examples (13 code blocks)
- +4Reference files are cited in the instructions (12 of 12)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.