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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

90%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

77%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-structured body with an exceptional gated workflow (preflight with validation and recovery loops) and clean reference routing. Its one real weakness is token efficiency: the critical guardrail rules (legal createModel values, never-assume-enabled, preflight steps) are each restated three to four times across the STOP section, providers section, and Best Practices, where one authoritative statement plus brief pointers would preserve all the safety value at a fraction of the tokens.

Suggestions

State the three legal `createModel` values once in the STOP section (the authoritative table) and reduce 'Available Providers and Models' and Best Practices #2–#3 to one-line pointers to it, cutting roughly 60 lines of repetition.

Replace Best Practice #1's full restatement of the preflight with a single sentence referencing the 'Mandatory Two-Step Preflight' section, keeping only the purchase-link behavior as the new information.

Consolidate the four occurrences of 'Never assume a model is already enabled' into one prominent statement in the preflight, leaving at most short inline reminders where the rule is directly exercised.

DimensionReasoningScore

Conciseness

The body is noticeably verbose through systematic rule repetition: the three legal `createModel` values are stated in full in the STOP section, again in 'Available Providers and Models', and again in Best Practices #2–#3; 'Never assume a model is already enabled' appears at four separate places; and Best Practice #1 restates the entire two-step preflight section nearly verbatim. Not a 1 — there is zero padding explaining concepts Claude already knows and most content is load-bearing — but the redundancy pushes it well below the midpoint ('penalize verbosity even if accurate').

2 / 5

Actionability

Guidance is fully executable: exact MCP call shapes with real parameters ('callCloudApi(service="tcb", action="DescribeEnvPostpayPackage", params={ EnvId })'), explicit pass conditions and status codes, a copy-paste user-facing purchase link, complete init snippets for both cloud-function and regular-server contexts, concrete timeout ranges (60–120s text, 900s image), and a working generateText example. Not a 4 — the only placeholders (in UpdateAIModel's Models array) are inherently dynamic values with explicit instructions for filling them.

5 / 5

Workflow Clarity

The preflight is sequenced Step 0 → ① → ② with explicit validation checkpoints (pass conditions on postpayPackageId prefix and status), failure branches with exact recovery actions (stop and surface the purchase message; jump to step 4 to enable a missing model), a casing fallback on InvalidParameter, and a full-replacement warning on the semi-destructive UpdateAIModel call. This matches the 5 anchor: clear sequence, explicit validation, and feedback loops for error recovery.

5 / 5

Progressive Disclosure

SKILL.md is a decision-time overview with detail correctly split into two existing, one-level-deep references (verified on disk), each clearly signaled with its contents ('generateText / streamText / generateImage examples, error-handling pattern, image parameters, TypeScript type definitions'; 'console flow + CreateAIModel'), and a closing Reference index. Nothing is nested deeper than one level and navigation is easy — a clear 5.

5 / 5

Total

17

/

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.

An exemplary description: it states the exact SDK and version floor, enumerates concrete capabilities and API entry points, provides explicit positive and negative triggers in natural user vocabulary, and disambiguates against sibling skills. Every clause carries information with no padding.

DimensionReasoningScore

Specificity

The description lists multiple concrete capabilities with exact API surface: 'image generation (ai.createImageModel + generateImage)', 'Text via ai.createModel with groups cloudbase, hunyuan-exp, or custom-*', 'model ids ... go in the `model` field of generateText/streamText', plus 'MUST run two-step preflight before code'. Coverage spans text generation, image generation, model selection, and gating requirements — comprehensive with no abstract filler.

5 / 5

Completeness

Both questions are explicitly answered: 'what' via 'Node.js backend AI via @cloudbase/node-sdk ... image generation ... Text via ai.createModel', and 'when' via the explicit 'Use this skill for ...' clause plus concrete trigger phrases. It also adds explicit negative triggers ('NOT for browser/Web ... or Mini Program'), matching the 5 anchor ('clearly and explicitly answers both what AND when with concrete trigger phrases').

5 / 5

Trigger Term Quality

Natural trigger vocabulary is comprehensive: runtime targets ('Node.js backend', 'cloud functions', 'CloudRun', 'serverless APIs'), framework names ('Express/Koa/NestJS'), task phrases users would actually say ('scheduled jobs', 'LLM proxies', 'agent orchestration'), plus concrete model ids ('deepseek-v4-flash, glm-5, kimi-k2.6') and the package name '@cloudbase/node-sdk'. Not clearly below the 5 anchor and clearly above the 4 anchor ('a few natural terms missing') — no meaningful term is absent for this domain.

5 / 5

Distinctiveness Conflict Risk

The niche is sharply bounded by runtime plane (server-side Node.js via one named SDK) and it explicitly routes conflicting cases to sibling skills ('use ai-model-web', 'use ai-model-wechat'), eliminating overlap risk with the closest related skills. Minimal conflict risk — a clear 5.

5 / 5

Total

20

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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/ai-model-nodejs/SKILL.md

Reviewed

Table of Contents

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