Conciseness

The body is mostly efficient operational guidance (file trees, naming rules, selector tables) rather than concepts Claude already knows, but it includes unnecessary weight: time-sensitive markers ('2026-03-10 实测验证 ✅', 'GPT-5.2 Pro') outside any deprecated section, quota trivia, and automation tables that duplicate the referenced shared-ref files. It fits 'mostly efficient but includes some unnecessary explanation or could be tightened' rather than the 4 anchor, whose over-explanation would be only minor.

Actionability

Guidance is largely executable: concrete directory layout, kebab-case naming rules, a full 8-slot prompt template, a 3-part consult document structure, and specific code/commands (execCommand('insertText'), DataTransfer file injection, exact CSS selectors like '[data-testid="deep-research-sidebar-item"]'). Minor gaps — some steps depend on operator actions and key details are deferred to external refs — keep it below the fully copy-paste-ready 5.

Workflow Clarity

Both modes have clearly sequenced steps (Mode A Steps 1–5, Mode B Steps 1–3) with explicit file outputs per step, a common-error/correction table, quality-gate criteria, and a verification step ('git log --oneline -1 显示刚才的 commit'). Some checkpoints are descriptive rather than executable checks (e.g., '对照实际 codebase 验证'), so it does not reach the explicit validate/fix/retry loop of the 5 anchor.

Progressive Disclosure

References to external files are one level deep and clearly signaled (../.cat-cafe-shared-refs/chatgpt-browser-automation.md etc.), but the skill bundle has no references/scripts/assets files, and substantial platform-automation reference material is inlined directly in SKILL.md even though the referenced external docs already exist — content that should be separate is inline, matching the 3 anchor rather than the well-split 4.

Specificity

Names the domain (多源深度调研管道) and multiple concrete capabilities — Web Deep Research, Coder 合成, 云端模型咨询 — plus concrete outputs ('调研报告 + 证据合成 或 咨询文档（含回填区）'). It lists several specific actions but stays at the component level rather than comprehensively covering the operations, so it matches the 'several specific actions; minor gaps' anchor and not the comprehensive 5.

Completeness

It explicitly answers both what (pipeline with named components and output artifacts) and when ('Use when: 技术问题需要多源调查、设计决策需要证据...'), with concrete trigger phrases and an additional 'Not for' exclusion clause — matching the anchor for clearly and explicitly answering both with concrete triggers.

Trigger Term Quality

Explicit triggers ('调研', 'research', '深度研究', '问一下 GPT Pro', '咨询云端') plus 'Use when: ...operator说"调研"/"research"' give good natural-term coverage a user would actually say. Common variations like 'deep research', '调查', or '查资料' are missing, keeping it below the comprehensive-synonyms anchor of 5 and above the sparse coverage of 3.

Distinctiveness Conflict Risk

The multi-source triangulation + cloud-consultation niche with an explicit 'Not for: 简单搜索（直接用 WebSearch）' boundary is mostly distinct from other skills. However, the broad trigger '调研/research' could still overlap with general search or research-adjacent skills, so it is not the minimal-conflict 5.