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本地知识库集成 - 文档检索、投喂、双轨模式切换

50

Quality

54%

Does it follow best practices?

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tessl review fix ./configs/microservice/bff-service/configs/agent-skills/clawhub/knowledge/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

58%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is admirably lean and well-organized for its size, but it functions as a command cheat-sheet rather than an operational skill: none of the four advertised operations has executable steps, and the document-feeding workflow has no sequence or validation. Adding concrete API call examples for search and a feed-then-verify workflow would address the two weak dimensions.

Suggestions

Add an executable example for the core search operation, e.g. the actual HTTP request against http://127.0.0.1:8001 (endpoint path, method, and response format), so actionability reaches concrete, copy-paste-ready guidance.

Document the 投喂 (document feeding) workflow as a numbered sequence with a validation step (e.g., verify document count via 知识库统计 after feeding), since batch ingestion without validation caps workflow clarity at 3.

Specify what '切换到本地知识库' / '切换到 AnythingLLM' actually do operationally (persisted setting, per-session flag, or API call) so mode switching is unambiguous.

DimensionReasoningScore

Conciseness

The body is ~20 lines with zero padding: a four-row command table and two concrete location facts ("E:/knowledge-base", "http://127.0.0.1:8001"), with no explanations of concepts Claude already knows. It matches the 'lean and efficient; every token earns its place' anchor, and there is nothing to trim that would push it toward 4.

5 / 5

Actionability

The body maps user phrases to intents ("查一下 xxx" → 搜索知识库) and gives a root path and API base URL, but provides no executable guidance for any operation — no API endpoint or request format for searching, no command or script for switching modes or feeding documents. This matches 'minimal concrete guidance; high-level hints but missing the specific steps to execute'; it is above 1 because the paths, URL, and exact command phrases are concrete, and below 3 because even pseudocode-level steps for the core actions are absent.

2 / 5

Workflow Clarity

No sequence exists for any operation: how a search is executed against the API, what document feeding (投喂) involves, or how mode switching takes effect is entirely unspecified, matching 'rough sequence present but many gaps; validation absent' (here the gaps swallow the sequence). It is not 1 because the command table does establish an unambiguous intent-to-action mapping for the simple lookup case, and the simple-skill exception to score 5 does not apply because the core actions are not unambiguous; the batch-like feeding operation also lacks any validation, which would cap this at 3 regardless.

2 / 5

Progressive Disclosure

This is a skill under 50 lines with no bundle files (references/, scripts/, assets/ do not exist) and no need for external references, and the body is organized into two well-labeled sections (使用方法, 文件位置), which per the rubric's simple-skill guidance earns a 5. There are no buried or nested references to penalize, and no inlined content that belongs in a separate file.

5 / 5

Total

14

/

20

Passed

Description

50%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description names a specific domain and three concrete capabilities, but it is a terse keyword list with no 'use when' trigger guidance and no natural user phrases, capping completeness and trigger quality at the midpoint. Adding an explicit trigger clause referencing the voice commands already documented in the body would lift most dimensions.

Suggestions

Add an explicit 'Use when...' (使用时机) clause, e.g. "Use when the user says '查一下', '知识库统计', or asks to search/switch the local knowledge base", to raise completeness above 3.

Include the natural trigger phrases from the body (查一下 xxx, 切换到本地知识库, 切换到 AnythingLLM, 知识库统计) so trigger_term_quality covers real user utterances instead of capability nouns only.

Mention AnythingLLM by name in the description to sharpen distinctiveness and reduce overlap risk with generic search/RAG skills.

DimensionReasoningScore

Specificity

The description names the domain ("本地知识库集成") and lists concrete actions ("文档检索、投喂、双轨模式切换"), matching the anchor for naming a domain with 1-2 concrete actions but not comprehensive coverage. It does not reach 4 because it omits several capabilities implied by the body (e.g., knowledge base statistics) and stays at a bare keyword list, and it is above 2 because the actions named are specific rather than generic.

3 / 5

Completeness

There is a recognizable 'what' (local knowledge base integration covering retrieval, document feeding, and dual-track mode switching) but no 'when' clause at all, which per the judging guidelines caps completeness at 3. It cannot be 4 without any trigger guidance, and it is above 2 because the 'what' is stated with concrete capability names rather than being vague.

3 / 5

Trigger Term Quality

Terms like "知识库" (knowledge base) and "文档检索" (document retrieval) are relevant keywords a user might plausibly say, matching the 'some relevant keywords but missing common variations' anchor. It is not 4 because natural user phrasings shown in the body ("查一下", "切换到本地知识库", "知识库统计") and synonyms/extensions are absent from the description, and it is above 2 because the keywords are domain-relevant rather than purely generic.

3 / 5

Distinctiveness Conflict Risk

"本地知识库" (local knowledge base) carves out a somewhat specific niche, but the description never names the concrete system involved (AnythingLLM appears only in the body) and could overlap with general RAG/search/document skills, matching the 'somewhat specific but could still overlap' anchor. It is below 4 because the distinctive dual-track trigger phrases are missing, and above 2 because it is not broadly generic like 'helps with documents'.

3 / 5

Total

12

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
UnicomAI/wanwu
Reviewed

Table of Contents

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