Content
85%Weight 40%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured, highly actionable operational skill with strong workflow sequencing, checkpoints, and clean one-level-deep progressive disclosure backed by real bundle files. The main weakness is conciseness: several algorithm rules are restated across the scenario, STOP, and anti-pattern sections and could be consolidated.
Suggestions
Consolidate the repeated algorithm rules (external-link placement, hashtag limits, 280-char cap) into one canonical location and cross-reference it from 场景A, the STOP checkpoint, and 反例黑名单 to remove the triple restatement.
Consider trimming the「$10K/hr级」framing and creator name list in the description, and similarly reduce any duplicated guidance in the body, to reclaim context budget.
The 实测微例 examples are useful but duplicate mechanics already stated in the scenarios; keep one or the other per rule to tighten the body.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient and largely earned content (X algorithm specifics, creator methodologies Claude would not know), but several rules are restated across sections — external-link placement appears in 场景A, the STOP checkpoint, and 反例黑名单 #1; the 280-char / hashtag limits are likewise repeated — so it could be tightened. Not a 3 because the redundancy competes with the context budget; not a 1 because there is no padding explaining concepts Claude already knows. | 2 / 3 |
Actionability | Highly concrete and executable: numbered Step flows, specific char limits「短推文控制120-130字符」「Thread 单条 ≤280」, named hook formulas (好奇缺口/可信度锚点/Value Equation), named tool fallbacks (computer-use → claude-in-chrome → manual), concrete file paths (user-data/{username}/tweets_{YYYYMMDD}.json), and baseline→round1 worked examples. Copy-paste-ready guidance throughout. | 3 / 3 |
Workflow Clarity | Multi-step processes are explicitly sequenced (Step 1–5 per scenario) with 【检查点】 gates, a dedicated STOP section of required pre-output questions, and a failure-mode fallback tree providing feedback loops (tool failure → switch method, validation gap → return to Step). Matches the clear-sequence-with-validation-and-checklists anchor. | 3 / 3 |
Progressive Disclosure | SKILL.md is a clear overview with a problem-routing table mapping each query type to specific references, an explicit loading principle「只加载当前场景需要的reference,不要一次全读」, and a Reference索引 table; all referenced files (writing-workshop, algorithm-niche, growth-monetization, quality-analytics, mental-models-heuristics, and the 6 research/*.md) verified to exist. The research/ tier is a justified, clearly-gated second level (「仅在需要追溯来源时读取」), not indirection. | 3 / 3 |
Total | 11 / 12 Passed |