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cloudbase-code-review

Code review and validation for CloudBase projects. After writing code for Web / miniprogram / CloudRun / cloud-function projects, call this skill to check for known pitfalls — auth guard misuse, missing database tables, RLS misconfiguration, storage domain setup, and SDK API misuse. Supports automated lint scripts (regex-based) + LLM semantic review.

Quality

83%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

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 with excellent progressive disclosure — a verified, one-level-deep reference bundle and clear navigation. Its weaknesses are moderate redundancy in the lint instructions, maintainer-oriented sections that inflate token cost, and a missing error-recovery loop after lint failures.

Suggestions

State the lint run instructions once (in Quick start) and reference them from the "How it works" table to remove the near-verbatim duplication.

Trim or relocate the "Rule boundary" and "Rule format" sections into RULES_INDEX.md, keeping only a one-line pointer, since they primarily serve skill maintainers rather than execution.

Add an explicit feedback step after lint runs (e.g. "If lint exits 1, read the flagged rule's 修复指引, fix the code, and re-run") to close the validation loop.

DimensionReasoningScore

Conciseness

Mostly tight tables and lists with no concept-teaching, but the lint copy-to-temp instructions are repeated near-verbatim in both the "How it works" table and "Quick start", and "Rule boundary"/"Rule format" lean toward maintainer meta-documentation. Not 4 because the duplication and meta sections go beyond "minor" over-explanation; not 2 because there is no padded explanatory content.

3 / 5

Actionability

Provides concrete file paths ("references/rules/cross-cutting/AUTH001.md"), a copy-paste command ("node cloudbase-lint.mjs --project-dir ."), and exact sections to read ("LLM 检查"). Not 5 because it omits what to do after lint reports issues and how to report findings; not 3 because the guidance is directly executable as written.

4 / 5

Workflow Clarity

Quick start gives a clear two-step sequence with the lint layer as a deterministic validation checkpoint and "inspect your code before claiming done" as a completion gate. Not 5 because there is no explicit fix-and-re-run feedback loop in the body for lint failures; not 3 because sequence and checkpoints are mostly explicit.

4 / 5

Progressive Disclosure

SKILL.md is a lean overview with all 10 referenced bundle files verified present, organized one hop deep by module (cross-cutting / postgresql / storage), plus a full link index and a RULES_INDEX.md matrix for navigation. Bulk rule content is appropriately deferred to reference files with no deep nesting.

5 / 5

Total

16

/

20

Passed

Description

92%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 strong description: it states concrete capabilities, an explicit post-implementation trigger, and a platform-scoped niche. Its only weakness is that a few natural synonym terms are absent, which slightly limits recall across varied user phrasings.

DimensionReasoningScore

Specificity

Lists five concrete check categories ("auth guard misuse, missing database tables, RLS misconfiguration, storage domain setup, and SDK API misuse") plus two review methods ("automated lint scripts (regex-based) + LLM semantic review"), which comprehensively covers the skill's bundle modules. Not 4 because coverage matches the actual rule set with no significant gaps.

5 / 5

Completeness

Explicitly answers both what ("Code review and validation for CloudBase projects... check for known pitfalls") and when ("After writing code for Web / miniprogram / CloudRun / cloud-function projects, call this skill"). Not 4 because the when clause is specific and concrete, not merely present.

5 / 5

Trigger Term Quality

Strong domain keywords a CloudBase user would naturally say ("CloudBase", "miniprogram", "CloudRun", "cloud-function", "auth guard", "RLS", "lint"), but a few natural synonyms are missing (e.g. "security rules", "TCB/Tencent CloudBase", "小程序"). Not 5 because synonym and variation coverage is good rather than comprehensive.

4 / 5

Distinctiveness Conflict Risk

"CloudBase projects" with enumerated platform-specific pitfalls creates a clear niche distinct from generic code-review skills. Not 4 because the platform qualifier means it is unlikely to trigger for the wrong skill.

5 / 5

Total

19

/

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

frontmatter_unknown_keys

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

Warning

relative_links

Relative link issues: 10 deeper-than-1-level

Warning

referenced_paths_exist

Referenced path issues: 16 deeper-than-1-level

Warning

Total

13

/

16

Passed

Repository

TencentCloudBase/CloudBase-AI-Toolkit

Path

config/source/skills/cloudbase-code-review/SKILL.md

Reviewed

Table of Contents

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