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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).

74

Quality

93%

Does it follow best practices?

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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.

The body is highly actionable and workflow-safe: exact MCP calls, pass/fail conditions, error-recovery branches, and appropriately deferred API detail in two real reference files. Its one weakness is token efficiency — the core rules (legal createModel values, never-assume-enabled, preflight) are restated three to four times across the STOP section, providers section, and Best Practices, inflating the file well beyond what the same information needs.

Suggestions

State the three legal createModel values once in the STOP section and have 'Available Providers and Models' and Best Practice #3 cross-reference it (e.g., 'See the createModel contract above') instead of restating the full rule and wrong-pattern list each time.

Trim Best Practices #1–2, which re-narrate the entire two-step preflight already detailed above — replace with a one-line reminder pointing back to the Mandatory Two-Step Preflight section.

Merge the duplicated framing between the STOP table and the 'Available Providers and Models' intro (both open with 'exactly three kinds of legal values'), keeping the table as the single canonical statement.

DimensionReasoningScore

Conciseness

The body never explains concepts Claude already knows (no 'what is a cloud function' filler), but it systematically repeats its own rules: the three legal createModel values appear in the STOP section, again in 'Available Providers and Models', and a third time in Best Practice #3; 'never assume a model is enabled' is restated in the decision procedure, preflight ②, the providers section, and Best Practices #1–2, which re-narrate the entire preflight. This fits 'mostly efficient but includes some unnecessary explanation or could be tightened' better than level 4 ('minor instances that could be trimmed') because the redundancy spans several sections, but better than level 2 since the padding is rule reinforcement rather than conceptual over-explanation.

3 / 5

Actionability

Guidance is fully executable throughout: exact MCP invocations with parameters ('callCloudApi(service="tcb", action="DescribeAIModels", params={ EnvId })'), explicit pass conditions ('postpayPackageId starts with pkg_tcb_tokencredits_', 'status is NOT in [3, 4]'), copy-paste-ready code for createModel/generateText and tcb.init, a concrete UpdateAIModel payload with the full-replacement Models[] shape, numeric timeout ranges (60–120 s text, 900 s image), and a purchase URL to surface on failure. This matches 'fully executable; copy-paste ready code or commands; specific examples cover the common cases' — nothing remains at the pseudocode or high-level-hint level.

5 / 5

Workflow Clarity

The two-step preflight is a clearly sequenced workflow (Step 0 → ① eligibility → ② group readiness) with explicit validation checkpoints (inspect AIModelGroups[].Models[] before any createModel, confirm exact Model spelling via DescribeManagedAIModelList) and feedback loops for error recovery: ❌ on the resource pack → stop and surface the purchase link; missing model → enable via UpdateAIModel then re-check; InvalidParameter → fall back to camelCase and 'trust the live response'. This matches 'clear sequence with explicit validation steps; feedback loops for error recovery' — above level 4, where some checkpoints would be implicit.

5 / 5

Progressive Disclosure

SKILL.md keeps the decision logic (routing, preflight, createModel rules) inline and defers bulk detail behind well-signaled, one-level-deep links that both exist in the bundle: [api-reference.md](references/api-reference.md) for method signatures/TypeScript types and [custom-onboarding.md](references/custom-onboarding.md) for the CreateAIModel flow, each described by content at the link site and enumerated in a closing 'Reference index'. This matches 'clear overview with well-signaled one-level-deep references; content appropriately split; easy navigation' — the references are one level deep with no chained indirection, so it exceeds level 4.

5 / 5

Total

18

/

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 what the skill does with concrete API entry points, when to use it with positive and negative triggers, and how it is distinguished from sibling skills, all in third-person/imperative trigger form without padding. Every clause carries load-bearing information (version pin, group names, model-id field placement, preflight mandate).

DimensionReasoningScore

Specificity

The description enumerates concrete, verifiable capabilities rather than abstractions: '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 the environments served ('cloud functions, CloudRun, Express/Koa/NestJS, serverless APIs, scheduled jobs, LLM proxies, agent orchestration') and a version pin '>=3.16.0'. This matches the anchor 'Lists multiple specific concrete actions; comprehensive coverage' — the text-generation path, image-generation path, runtime targets, and a mandatory preflight step are all named, so it is not the level-4 anchor, which requires minor gaps in coverage.

5 / 5

Completeness

Both questions are answered explicitly: the 'what' ('The only SDK supporting image generation… Text via ai.createModel… model ids go in the `model` field') and the 'when' ('Use this skill for Node.js backend AI…', reinforced by negative triggers 'NOT for browser/Web (use ai-model-web) or Mini Program (use ai-model-wechat)'). This matches the level-5 anchor 'clearly and explicitly answers both what AND when with concrete trigger phrases'; it is not level 4, where the 'when' could be more explicit — here both positive and negative trigger guidance is concrete.

5 / 5

Trigger Term Quality

Natural user phrasings are covered broadly with synonyms: 'Node.js backend AI', 'cloud functions', 'CloudRun', 'serverless APIs', 'scheduled jobs', 'LLM proxies', 'agent orchestration', 'image generation', plus concrete model names users would actually say ('deepseek-v4-flash, glm-5, kimi-k2.6') and the SDK package name '@cloudbase/node-sdk'. This meets the 'comprehensive coverage of natural terms including synonyms' anchor; it is clearly above level 4 ('good keyword coverage; a few natural terms missing') because both the platform vocabulary and the concrete model-name triggers users mention are present.

5 / 5

Distinctiveness Conflict Risk

The niche is sharply defined by runtime plane (Node.js server-side via '@cloudbase/node-sdk') and the description actively routes adjacent cases away: 'NOT for browser/Web (use ai-model-web) or Mini Program (use ai-model-wechat)'. Claims like 'The only SDK supporting image generation' further separate it from siblings. Minimal conflict risk, matching the level-5 'clear niche with distinct triggers' anchor rather than level 4, which tolerates minor overlap with closely related skills.

5 / 5

Total

20

/

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/.claude/skills/ai-model-nodejs/SKILL.md

Reviewed

Table of Contents

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