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interview-cheatsheet

Generate a long-form Chinese interview-prep cheat sheet on a specific ML/LLM topic — formulas with derivations, from-scratch PyTorch code, comparison tables, and 25 高频面试题 (L1 必会 / L2 进阶 / L3 顶级 lab). Use when the user says '写面试 cheat sheet', '写一份 X 教程', '帮我准备 Y 面试题', '出一份 X 速查', or wants a 600-1000 line Chinese tutorial on a specific ML topic.

Quality

93%

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

88%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.

An exceptionally actionable, well-sequenced workflow with strong validation feedback loops and no filler explanations. The main weakness is structure: everything lives inline in one long file rather than being split across reference files, plus a few trimmable narrative sections.

Suggestions

Move the Step 3 reviewer prompt and the Step 6 audit-trail JSON template into a references/ file (e.g. references/reviewer-prompt.md and references/audit-format.json), keeping only the invocation contract inline in SKILL.md.

Trim or compress the opening Selectable Reviewers blockquote and the Key invariants table — both partially duplicate information stated in the Workflow steps and Provenance sections.

Drop the anecdotal provenance details (specific May 2026 tutorial round counts) in favor of the already-stated convergence heuristic, keeping the file focused on forward-looking instructions.

DimensionReasoningScore

Conciseness

The body is dense operational guidance with almost no explanation of concepts Claude already knows, but a few sections could be trimmed: the opening reviewer-routing blockquote is opaque, the "Key invariants" table recaps the workflow steps, and the Provenance section includes anecdotal narrative ("the Video Generation tutorial (May 2026) went to 5 rounds…"). This fits anchor 4 (efficient, minor trimmable instances) rather than 3, since nothing is genuinely redundant filler.

4 / 5

Actionability

Fully executable throughout: the exact `render_html.py` command with all flags, a copy-paste reviewer prompt with a 10-check JSON contract, a concrete audit-trail JSON template, a verbatim final-report format, and good/bad topic-scoping examples. Anchor 5 — copy-paste ready and covers the common cases.

5 / 5

Workflow Clarity

Steps 1–7 are clearly sequenced with explicit validation gates (PASS/WARN/FAIL verdicts), a fix-and-reloop rule with fresh-thread enforcement, convergence/loop-detection heuristics, and a render-stage review gate — a textbook feedback loop. The generation task is not destructive, so no validation cap applies.

5 / 5

Progressive Disclosure

Well-sectioned with clearly signaled paths, but it is a ~250-line monolith whose reviewer prompt, audit JSON schema, and report template could live in reference files; the only file references point outside the bundle (`../shared-references/reviewer-backends.md`, `docs/tutorials/attention_tutorial.md`) and no `references/` directory exists. Anchor 4 — good structure with minor organization gaps, not 3 since references that do exist are clearly signaled and there are no nested reference chains.

4 / 5

Total

18

/

20

Passed

Description

100%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.

A model description: concrete deliverables, explicit bilingual trigger phrases covering what and when, and a distinct niche. It avoids buzzwords and over-claims while staying compact.

DimensionReasoningScore

Specificity

The description enumerates the full set of concrete deliverables — "formulas with derivations, from-scratch PyTorch code, comparison tables, and 25 高频面试题 (L1 必会 / L2 进阶 / L3 顶级 lab)" plus a 600-1000 line length target — comprehensive coverage with no vague filler.

5 / 5

Completeness

It explicitly answers both 'what' (generate a long-form Chinese cheat sheet with the listed deliverables) and 'when' ("Use when the user says… or wants a 600-1000 line Chinese tutorial") with concrete trigger phrases, matching the anchor-5 example structure.

5 / 5

Trigger Term Quality

It quotes four natural user phrasings users would actually say ('写面试 cheat sheet', '写一份 X 教程', '帮我准备 Y 面试题', '出一份 X 速查') plus English variants ('interview-prep cheat sheet', 'Chinese tutorial'), covering synonyms across both languages.

5 / 5

Distinctiveness Conflict Risk

It carves a clear niche — long-form Chinese ML/LLM interview-prep cheat sheets — with distinctive quoted triggers unlikely to fire for unrelated skills.

5 / 5

Total

20

/

20

Passed

Validation

81%

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

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

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

Warning

relative_links

Relative link issues: 1 missing, 1 suspicious

Warning

Total

13

/

16

Passed

Repository

wanshuiyin/Auto-claude-code-research-in-sleep

Path

skills/interview-cheatsheet/SKILL.md

Reviewed

Table of Contents

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