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cloudrun-development

CloudBase Run backend development rules (Function mode/Container mode). Use this skill when deploying backend services that require long connections, multi-language support, custom environments, AI agent development, or migrating existing/GitHub apps that need VPC access to MySQL/PostgreSQL/Redis. Also use when diagnosing CloudRun container deploy failures (deploy_failed, readiness/probe failed, image won't start, docker.io pull loops) or a deploy stuck behind a running deploy task. For stateless HTTP services, prefer HTTP cloud functions.

Quality

83%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

81%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 delivers highly actionable, well-sequenced operational guidance with strong validation and error-recovery loops, backed by real one-level-deep references. Its main cost is token weight: systematic cross-section repetition and English/Chinese duplication of the same decision guidance inflate the file without adding information.

Suggestions

State each rule once in its canonical section and cross-reference it elsewhere (e.g., keep the InitialDelaySeconds prohibition only in the Container deploy failure SOP and link from gotchas/troubleshooting) instead of restating it in five places.

Collapse the English/Chinese duplication: pick one language per section (or one as the canonical text with the other only where terminology matters), which would shrink the decision gates and mode-selection guidance substantially.

Move the Log query SOP, Deploy-task SOP tables, and the tool-action parameter documentation into a reference file (e.g., references/tool-routing-and-logs.md), keeping only routing rules and triggers in SKILL.md.

DimensionReasoningScore

Conciseness

The body is dense with high-signal operational content (no basic-concept padding), but key messages repeat across sections: 'do not raise InitialDelaySeconds' appears in gotchas, the checklist, the deployment sequence, the SOP, and troubleshooting; the CloudRun-vs-HTTP-function decision and the credential gate each appear three-plus times; and bilingual English/Chinese duplication (e.g., the 云托管 vs HTTP 云函数 and decision-gate sections) doubles the same guidance. This matches 'mostly efficient but includes some unnecessary explanation or could be tightened'. Not 4 because the repetition is systematic rather than a few trimmable instances; not 2 because nearly all content is platform-specific and non-inferable rather than padded explanation.

3 / 5

Actionability

Guidance is fully executable throughout: exact tool calls with parameters (`manageCloudRun(action="initEnv", envId=...)`, `queryCloudRun(action="envStatus")`), copy-paste JSON deploy payloads with concrete serverConfig values, runnable shell sequences (docker pull/tag/login/push), and a Dockerfile snippet. Specific examples cover the common cases (init, local run, deploy without VPC, deploy with VPC, imageUrl deploy), matching the score-5 anchor.

5 / 5

Workflow Clarity

The deployment sequence is a numbered checklist with explicit validation checkpoints (poll envStatus until Status=normal, verify detail output + DB connectivity, verify credentials with a real SDK read twice), and failure paths have feedback loops with branching tables (Deploy-task SOP, two-log-pull liveness comparison, Container deploy failure SOP ordering docs → logs → config). The destructive operation (delete) requires explicit confirmation and force:true, satisfying the destructive-operations cap. This matches the score-5 anchor's explicit validation, error-recovery loops, and checklists.

5 / 5

Progressive Disclosure

Structure is good: the two reference files (references/vpc-and-database.md, references/image-deploy-troubleshooting.md) are real, one level deep, clearly signaled at point of need ('also read... when'), behavior summaries stay in SKILL.md while detail tables live in the references, and a Reference index closes the file — matching the score-4 anchor. Not 5 because the ~450-line main body inlines material that could be split out (full tool-action parameter documentation, Log query SOP, Deploy-task SOP tables, and the credential decision gate), leaving the overview heavier than a clear 'overview + well-signaled pointers' shape.

4 / 5

Total

17

/

20

Passed

Description

78%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 with explicit, concrete 'use when' triggers covering deployment, migration, and failure-diagnosis scenarios, and good self-disambiguation against HTTP cloud functions. Its main weakness is that the capability statement ('backend development rules') is thinner than its trigger list, and a few natural trigger terms (WebSocket/SSE, container) are missing.

DimensionReasoningScore

Specificity

Concrete triggers like 'deploying backend services that require long connections, multi-language support... VPC access to MySQL/PostgreSQL/Redis' and 'diagnosing CloudRun container deploy failures (deploy_failed, readiness/probe failed, image won't start, docker.io pull loops)' name specific scenarios, matching the 'several specific actions; minor gaps' anchor. Not 5 because the 'what' half ('CloudBase Run backend development rules') is generic and doesn't enumerate the concrete actions the skill performs; not 3 because coverage of use cases clearly exceeds 1-2 actions.

4 / 5

Completeness

Both halves are present: 'what' ('CloudBase Run backend development rules (Function mode/Container mode)') and an explicit 'when' ('Use this skill when deploying... Also use when diagnosing...'), plus a negative-scope pointer ('For stateless HTTP services, prefer HTTP cloud functions'). Not 5 because the 'what' is broad ('development rules') without stating the concrete capabilities; the 'when' is explicit and specific, matching the score-4 anchor exactly.

4 / 5

Trigger Term Quality

Includes natural user-facing phrases such as 'deploying backend services', 'long connections', 'AI agent development', 'migrating existing/GitHub apps', 'MySQL/PostgreSQL/Redis', 'image won't start', and 'docker.io pull loops' — good keyword coverage matching the score-4 anchor. Not 5 because common variations like 'WebSocket', 'SSE', 'container', 'tcbr', or '云托管' are absent, leaving a few natural terms users would say uncovered.

4 / 5

Distinctiveness Conflict Risk

The description is tightly scoped to CloudBase Run ('CloudRun container deploy failures', 'VpcConf'-adjacent VPC database access) and even disambiguates against the closest sibling ('For stateless HTTP services, prefer HTTP cloud functions'), giving a clear niche with minimal conflict risk — a direct match to the score-5 anchor. Score 4 would require noticeable overlap with a closely related skill, which is not the case given the platform-specific product names.

5 / 5

Total

17

/

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

TencentCloudBase/CloudBase-AI-Toolkit

Path

config/source/skills/cloudrun-development/SKILL.md

Reviewed

Table of Contents

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