BD zh-knowledge-manager
中文 AI 增强知识管理。PREFIX 确定性分类 + hash/语义去重 + jieba 自动标签 + LLM 对话知识提取。
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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 · 3
✓ No critical or high findings
Medium and low: 3
-
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:25High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…dNm+w/2fIz…imP+QNz605/XnjF…qBg==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:113High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…Ufq+nJ5J/kzXjkfbr/1WY6…v72/wIx/jn7NoXfm/UPuJ…C6w==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:289High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…LYU+CX9r…iU1/AKbT…lBQ==",
detector
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")
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
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 100Steps. 16 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 429 tokens
- 100Running it twice. No mutating operations
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 64: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 7 headings
- +3Step-by-step instructions: 16 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.
External checks
ClawHub: clean
This is a coherent knowledge-management skill with local writes and optional AI API use, but users should treat AI extraction and semantic deduplication as sending selected content to configured providers.
LLM: benign (high) · VirusTotal: benign · 28 May 2026