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ai-model-nodejs

Use this skill for Node.js backend AI via @cloudbase/node-sdk (>=3.16.0) — cloud functions, CloudRun, Express/Koa/NestJS, serverless APIs, scheduled jobs, LLM proxies, agent orchestration. The only SDK supporting image generation (ai.createImageModel + generateImage). Text via ai.createModel with groups cloudbase, hunyuan-exp, or custom-*; model ids (e.g. deepseek-v4-flash, glm-5, kimi-k2.6) go in the `model` field of generateText/streamText. MUST run two-step preflight before code — see body. NOT for browser/Web (use ai-model-web) or Mini Program (use ai-model-wechat).

72

Quality

88%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is ai-model-nodejs in TencentCloudBase/CloudBase-AI-Toolkit

SKILL.md
Quality
Evals
Security

Quality

Content

85%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.

A highly actionable, well-sequenced skill body with strong validation checkpoints and clean progressive disclosure of detailed material into reference files. Its main weakness is deliberate repetition of the createModel and enablement guidance across multiple sections, which inflates token cost.

Suggestions

Consolidate the three-legal-`createModel`-values rule into one authoritative section (e.g. the STOP table) and have later sections reference it rather than re-stating it in Available Providers and Best Practice #3.

Merge the repeated 'never assume a model is already enabled' guidance into a single canonical statement to reduce redundancy across the preflight, Available Providers, and Best Practices sections.

Trim the Available Providers section's re-explanation of DescribeAIModels/DescribeManagedAIModelList/UpdateAIModel, which largely restates the preflight ② workflow.

DimensionReasoningScore

Conciseness

The body is dense and assumes Claude's competence (no explaining of basic concepts), but the three-legal-`createModel`-values rule and the "never assume a model is enabled" guidance are each repeated three or more times across the STOP, Available Providers, and Best Practices sections, so it could be tightened.

3 / 5

Actionability

Provides exact executable MCP calls with full params (callCloudApi(service="tcb", action="DescribeAIModels", params={EnvId})), copy-paste init and call code, and a concrete numbered decision procedure covering the common cases.

5 / 5

Workflow Clarity

The mandatory two-step preflight is clearly sequenced with explicit pass conditions, ❌ stop / ✅ proceed checkpoints, error-recovery feedback (InvalidParameter → camelCase fallback), and a self-verify step (Best Practice #13).

5 / 5

Progressive Disclosure

Body serves as the overview while the bulk API reference and custom onboarding are externalized into two real, well-signaled one-level-deep reference files (references/api-reference.md, references/custom-onboarding.md), with a closing reference index for navigation.

5 / 5

Total

18

/

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 highly specific, well-scoped description that clearly states both capability and trigger conditions, with explicit negative routing to sibling skills. The only soft spot is slightly technical phrasing in the trigger terms.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "cloud functions, CloudRun, Express/Koa/NestJS, serverless APIs, scheduled jobs, LLM proxies, agent orchestration" plus image generation and text generation — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both what ("Node.js backend AI via @cloudbase/node-sdk", image/text generation, preflight) and when ("Use this skill for…") with concrete trigger phrases and explicit exclusions ("NOT for browser/Web… or Mini Program").

5 / 5

Trigger Term Quality

Good natural-term coverage ("Node.js backend AI", "cloud functions", "CloudRun", "serverless APIs", "image generation") plus concrete model ids (deepseek-v4-flash, glm-5, kimi-k2.6), though phrasing leans technical and a few common user phrasings are not present.

4 / 5

Distinctiveness Conflict Risk

Scoped to "Node.js backend AI via @cloudbase/node-sdk" with explicit routing to ai-model-web and ai-model-wechat for other planes, giving a clear niche and minimal conflict risk.

5 / 5

Total

19

/

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.

Validation15 / 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
Reviewed

Table of Contents

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