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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. Only SDK supporting image generation (ai.createImageModel + generateImage). Text models via ai.createModel with groups cloudbase, hunyuan-exp, or custom-*. Model IDs (deepseek-v4-flash, deepseek-v3.2, hunyuan-2.0-instruct-20251111, glm-5, kimi-k2.6) go in the model field of generateText/streamText. MUST run two-step preflight before code — see body. Keywords: backend, 云函数, 云托管, serverless, LLM proxy, agent orchestration, generateText, streamText, generateImage, createModel, hunyuan-image, Token Credits, TokenHub, Hunyuan, DeepSeek, GLM, Kimi, MiniMax. NOT for browser/Web (use ai-model-web) or Mini Program (use ai-model-wechat).

71

Quality

88%

Does it follow best practices?

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SecuritybySnyk

High

Do not use without reviewing

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

SKILL.md
Quality
Evals
Security

Quality

Content

77%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable and has an excellent, explicitly-validated preflight workflow, but it is held back by repetition of the createModel/preflight rules across multiple sections and by a monolithic structure with no reference files for a skill this large. Tightening redundancy and splitting the API/type reference into a bundled file would lift both weak dimensions.

Suggestions

Consolidate the createModel legal-values rule into one authoritative section and have later sections (Available Providers, Decision Procedure, Best Practices #3) reference it instead of restating it, to reduce token redundancy.

Move the Type Definitions and the Available Providers/Models catalog into a bundled references/ file (e.g. references/api-reference.md) linked once from the body, so progressive disclosure splits detail one level deep instead of keeping ~150 lines of reference material inline.

Trim the 13-item Best Practices list to the items that add information not already covered in the preflight and code sections; right now several items restate earlier guidance.

DimensionReasoningScore

Conciseness

The material is SDK-specific and proprietary (not concepts Claude already knows), so it earns its place — but the three legal createModel values and the two-step preflight are restated three to four times (STOP section, Available Providers, Decision Procedure, Best Practices #1/#3), and the 13-item Best Practices section largely re-summarizes earlier sections. This is 'mostly efficient but could be tightened', not 'every token earns its place'.

2 / 3

Actionability

Fully executable, copy-paste-ready guidance throughout: npm install commands, tcb.init + generateText/streamText/generateImage code, exact callCloudApi(service, action, params) MCP invocations, and complete TypeScript interfaces for inputs/outputs. Nothing is pseudocode or abstract.

3 / 3

Workflow Clarity

The Mandatory Two-Step Preflight is an explicitly sequenced workflow (Step 0 env ID → preflight ① eligibility → preflight ② group readiness) with pass/fail branches ('Not satisfied → stop writing code', 'Satisfied → proceed'), a DescribeAIModels→UpdateAIModel feedback loop, a full-replacement Models warning, and a self-verify step (#13: tsc + build + real invoke, confirm usage.total_tokens > 0). This matches the clear-sequence-with-explicit-validation anchor.

3 / 3

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ all absent) despite a ~450-line body. Sections are well organized, but Type Definitions, the Available Providers/Models catalog, and Best Practices are reference-grade content kept fully inline that could be split into one-level-deep reference files; the only external links point to sibling skills via URL, not to detail files for this skill. This fits 'content that should be separate is inline' rather than 'appropriately split'.

2 / 3

Total

10

/

12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is strong across all four dimensions: concrete actions, natural trigger keywords, explicit when/when-not guidance, and clear distinctiveness from sibling web/mini-program skills. Its only weakness is verbosity/padding (a long packed string with a keyword list), but none of the four dimensions penalize description length directly.

DimensionReasoningScore

Specificity

Lists multiple concrete actions and domains — 'cloud functions, CloudRun, Express, Koa, NestJS, serverless APIs, scheduled jobs, LLM proxies', image generation, and text models via ai.createModel — plus specific model IDs (deepseek-v4-flash, glm-5, kimi-k2.6). These are concrete, specific actions rather than vague language, matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

It explicitly answers both 'what' (Node.js backend AI via @cloudbase/node-sdk, image generation, text models) and 'when' with an explicit 'Use this skill for...' trigger clause, plus a 'NOT for browser/Web ... use ai-model-web' exclusion. The presence of an explicit trigger clause keeps it from the cap-of-2 case for missing trigger guidance.

3 / 3

Trigger Term Quality

A dedicated 'Keywords:' span provides broad natural-phrase coverage a user would actually say — backend, serverless, LLM proxy, Hunyuan, DeepSeek, GLM, Kimi, MiniMax, plus 云函数/云托管 — matching the 'good coverage of natural terms' anchor rather than only technical jargon.

3 / 3

Distinctiveness Conflict Risk

It carves a clear runtime-plane niche (Node.js server-side) and explicitly redirects adjacent runtimes to other skills — 'NOT for browser/Web (use ai-model-web) or Mini Program (use ai-model-wechat)' — making conflict with sibling skills unlikely.

3 / 3

Total

12

/

12

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

14

/

16

Passed

Repository
TencentCloudBase/CloudBase-AI-Toolkit
Reviewed

Table of Contents

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