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smart-search-tables

找表/找数端到端编排:在元数据型知识网络下用 ontology bkn object-type query 检索表/视图实例, 再在职责型知识网络下检索相关部门职责与治理边界,最后汇总为中文结论 (候选表 + 职责要点 + 下一步)。当用户问「表在哪、哪个视图、数据资产归属、谁负责这类数据」时使用。 所有 ontology CLI 执行均委托 ontology-core 完成;本 skill 不直接执行 CLI。

64

Quality

77%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./configs/microservice/bff-service/configs/agent-skills/ontology/smart-search-tables/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

71%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 well-structured and actionable, with a clear fixed workflow, real feedback loops for empty/error cases, and excellent progressive disclosure via verified one-level-deep references. The main weakness is conciseness: the delegation and no-token constraints are restated multiple times and could be consolidated.

Suggestions

Consolidate the repeated 'Never directly execute CLI — delegate to ontology-core' and '无须 token / 不出现 --token' reminders into a single stated-once constraint block; reference it rather than restating verbatim in the body and every reference file.

Make the step-1-to-step-2 handoff checkpoint explicit (e.g., 'if step 1 yields no department/topic clues, fall back to the user's original terms or ask a clarifying question before calling the duty KN') instead of leaving it implied.

In the main body, show one minimal complete condition-json example inline so the command form is copy-paste-ready without requiring a jump to metadata-search.md.

DimensionReasoningScore

Conciseness

The body is mostly operational and free of concepts Claude already knows, but the delegation reminder ('Never 直接执行 CLI,委托 ontology-core') and the '无须 token / 不出现 --token' constraint are repeated verbatim several times across the body and each reference, which could be tightened.

3 / 5

Actionability

Provides concrete command forms (`ontology --user-id <accountId> bkn object-type query <kn_id> <ot-id> '<condition-json>' [--limit n]`) and the references carry full, copy-paste-ready bash with complete condition-json bodies and example values; minor gaps come from the deliberate placeholder-only form in the main body.

4 / 5

Workflow Clarity

A fixed, clearly sequenced 2-step-query + summarize pipeline with a progress checklist and feedback loops (empty result → rewrite `search`/switch KN/clarify; command error → report honestly, never fabricate); this is read-only retrieval so the destructive/batch validation cap does not apply, but an explicit 'verify step 1 returned clues before step 2' checkpoint is only implied.

4 / 5

Progressive Disclosure

SKILL.md is a concise overview with a '必读 references(按步骤)' table signaling three one-level-deep reference files (metadata-search.md, duty-search.md, tool-examples.md), all verified present; content is appropriately split (overview / per-step command detail / end-to-end example) with easy navigation.

5 / 5

Total

16

/

20

Passed

Description

83%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 is strong: it states concrete actions with the actual subcommand, gives an explicit 'Use when…' trigger clause with natural Chinese phrases, and carves out a distinct niche. Voice is third-person throughout. It is held back only by minor specificity/trigger-coverage gaps rather than any structural weakness.

DimensionReasoningScore

Specificity

Names several concrete actions — '用 ontology bkn object-type query 检索表/视图实例', '检索相关部门职责与治理边界', '汇总为中文结论(候选表 + 职责要点 + 下一步)' — including the specific subcommand, with only minor gaps (the auxiliary `list` command is not mentioned).

4 / 5

Completeness

Explicitly answers both: 'what' ('找表/找数端到端编排…检索表/视图实例…检索相关部门职责…汇总为中文结论') and 'when' ('当用户问「表在哪、哪个视图、数据资产归属、谁负责这类数据」时使用') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Includes natural Chinese trigger phrases a user would actually say — 「表在哪、哪个视图、数据资产归属、谁负责这类数据」 — covering synonyms (表/视图, 归属/谁负责), though a few common variations are absent.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (locating tables/views and data-asset ownership in ontology knowledge networks) with distinct triggers; minor overlap risk with the related smart-ask-data skill, which it explicitly distinguishes (metrics/SQL 取数 vs. 找表/定位).

4 / 5

Total

17

/

20

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 1 missing, 7 suspicious

Warning

Total

14

/

16

Passed

Repository
UnicomAI/wanwu
Reviewed

Table of Contents

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