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iterative-retrieval

逐步优化上下文检索以解决子代理上下文问题的模式

47

Quality

50%

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tessl review fix ./docs/zh-CN/skills/iterative-retrieval/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

56%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 presents a well-sequenced 4-phase retrieval loop with concrete scoring thresholds and two worked examples that make the pattern easy to follow. Its weaknesses are pseudocode that calls undefined helper functions, some duplication (diagram, repeated relevance tiers, repeated prompt block), and a monolithic single-file layout at ~215 lines with no progressive-disclosure structure.

Suggestions

Make the code executable or explicitly justify it as pseudocode: define or stub the helper functions (retrieveFiles, scoreRelevance, extractPatterns, hasCriticalGaps, mergeContext), or reduce the code blocks to the essential loop logic.

Trim duplication: drop the decorative ASCII diagram (the numbered phases already convey the cycle) and state the relevance tiers once instead of in both code comments and the 评分标准 list.

At ~215 lines, move the two worked examples into a references/EXAMPLES.md and link it from a short section, giving the SKILL.md a leaner overview with one-level-deep references.

DimensionReasoningScore

Conciseness

The body is mostly efficient — it does not re-explain what agents or retrieval are — but the ASCII box diagram adds no information over the numbered phases, the relevance tiers are stated twice (in code comments and again as the 评分标准 list), and the 与智能体集成 prompt block repeats the phase list. This matches 'Mostly efficient but includes some unnecessary explanation or could be tightened' rather than the lean 4-5.

3 / 5

Actionability

The JavaScript examples depend on undefined helpers (retrieveFiles, scoreRelevance, explainRelevance, extractPatterns, hasCriticalGaps, mergeContext), so they are illustrative pseudocode rather than executable code — precisely the anchor-3 description. The concrete thresholds (relevance >= 0.7, max 3 cycles) and the ready-to-embed agent prompt keep it above 2.

3 / 5

Workflow Clarity

The 4-phase loop (调度→评估→优化→循环) is clearly sequenced with an explicit stopping rule — at least 3 files at relevance >= 0.7 with no critical gaps, hard-capped at 3 cycles — and the two worked examples walk every cycle, giving a real validation checkpoint. It falls short of 5 because there is no guidance for the failure case (e.g. zero relevant files after all cycles).

4 / 5

Progressive Disclosure

This is a single-file skill with no references/, scripts/, or assets/ bundle and no well-signaled pointer files; sections are cleanly organized, but at ~215 lines the worked examples and best practices are candidates for a separate file, and the only external pointers are a bare X post link and skill names without paths. This matches 'Some structure but could be better organized' rather than the clear one-level-deep reference structure of 4-5.

3 / 5

Total

13

/

20

Passed

Description

45%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 identifies a specific niche (subagent context retrieval in multi-agent workflows) but offers only one generic action and, critically, contains no 'when to use' trigger guidance, capping completeness. Adding explicit trigger phrases and naming the concrete capabilities (dispatch, evaluate relevance, refine queries) would lift it substantially.

Suggestions

Add an explicit 'Use when...' clause in the description, e.g. 'Use when spawning subagents that need codebase context, building multi-agent workflows, or hitting context-too-large / missing-context failures'.

Replace the single abstract phrase with 2-3 concrete capabilities, e.g. 'Dispatch broad retrieval queries, score file relevance, and iteratively refine search terms to assemble subagent context'.

Include natural trigger synonyms users would say — 'multi-agent', 'sub-agent', 'RAG-style retrieval', 'context window' — to improve trigger matching and distinctiveness.

DimensionReasoningScore

Specificity

"逐步优化上下文检索以解决子代理上下文问题的模式" names the domain (context retrieval for subagents) but the only action offered is the generic 'refine retrieval', with no concrete capabilities listed — matching the anchor 'Names the domain but actions are minimal or generic'. It is not a 1 because it is not pure abstraction, and not a 3 because no concrete, enumerable actions (e.g. 'dispatch, evaluate, refine queries') appear.

2 / 5

Completeness

The 'what' is stated (an iterative pattern for refining context retrieval for subagents), but there is no 'Use when...' or equivalent trigger clause anywhere in the description, which the rubric explicitly caps at 3. It is not a 2 because the 'what' is not vague — it names a specific mechanism and problem.

3 / 5

Trigger Term Quality

Terms like "上下文" (context), "检索" (retrieval), and "子代理" (subagent) are words a user building multi-agent workflows would naturally say, but common variations and synonyms ('multi-agent', 'RAG', 'sub-agent', 'token usage') are absent, matching 'Some relevant keywords but missing common variations or synonyms' rather than the comprehensive coverage of 4.

3 / 5

Distinctiveness Conflict Risk

The subagent-orchestration niche is fairly specific, but the description could still trigger for general retrieval, RAG, or context-management skills — matching 'Somewhat specific but could still overlap with similar skills' rather than the clear niche with minimal conflict risk of 5.

3 / 5

Total

11

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
affaan-m/ECC
Reviewed

Table of Contents

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