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ai-model-web

Use this skill when a browser/Web app (React, Vue, Next, Nuxt, static sites, SPAs, dashboards, AI chat UI, 页面, 前端, 网页) needs AI models via @cloudbase/js-sdk. Default routing for Web/frontend AI — call directly from the browser, do NOT propose a Node.js proxy. Covers generateText and streamText; models via ai.createModel with groups cloudbase, hunyuan-exp, or custom-*, model id in the `model` field. MUST run two-step preflight before code — see body. NOT for Node.js backend (use ai-model-nodejs), Mini Program (use ai-model-wechat), or image generation (Node SDK only).

72

Quality

90%

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-web in TencentCloudBase/CloudBase-AI-Toolkit

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.

Highly actionable and workflow-driven content with executable code, exact MCP calls, and a well-gated preflight process. The main weakness is redundancy — the createModel and preflight rules are repeated across several sections — and some bulky reference material is inlined rather than moved into separate files.

Suggestions

Consolidate the createModel-argument rules into a single authoritative section (STOP) and have Available Providers, Custom onboarding, and Best Practices link back to it instead of restating it.

Move the Type Definitions and the full Available Providers/Models catalog into a references/ file (e.g. REFERENCE.md) and keep SKILL.md as an overview pointing to it, reducing the inlined bulk.

Trim the Best Practices list to items not already covered inline (preflight, createModel rules, anonymous auth) to cut repetition and save tokens.

DimensionReasoningScore

Conciseness

Mostly efficient and free of basic-concept padding, but the createModel argument rules are restated across the STOP, Available Providers, Custom onboarding, and Best Practices sections, and Best Practices rehashes preflight and anonymous-auth guidance already covered above.

3 / 5

Actionability

Copy-paste-ready executable blocks for init, generateText, streamText, and error handling, plus exact callCloudApi invocations with full PascalCase params and a TypeScript type-definitions section covering the common cases.

5 / 5

Workflow Clarity

The two-step preflight is a clearly sequenced multi-step process with explicit validation gates (eligibility pass conditions, 'stop writing code and surface this to the user', 'Do not write createModel yet') and feedback loops (eligibility fail → recheck; model missing → DescribeManagedAIModelList → UpdateAIModel).

5 / 5

Progressive Disclosure

Well-organized with clear section headers and clearly-signaled one-level-deep sibling-skill references (relative paths with rationale), but the bulky type definitions and full provider/model catalog are inlined rather than split into reference files, leaving minor organization gaps.

4 / 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.

A strong, specific description that names concrete API actions, packs in natural trigger terms (including bilingual synonyms), and cleanly answers both what and when while explicitly fencing off sibling skills. It is dense but every clause earns its place.

DimensionReasoningScore

Specificity

Lists multiple concrete API actions — 'Covers generateText and streamText', 'models via ai.createModel with groups cloudbase, hunyuan-exp, or custom-*', 'model id in the `model` field', 'two-step preflight' — giving comprehensive coverage of the skill's surface.

5 / 5

Completeness

Explicitly answers both what ('generateText and streamText', 'ai.createModel') and when ('Use this skill when a browser/Web app ... needs AI models', 'Default routing for Web/frontend AI') with concrete trigger phrases and negative boundaries.

5 / 5

Trigger Term Quality

Comprehensive natural-term coverage with synonyms in two languages — 'browser/Web app (React, Vue, Next, Nuxt, static sites, SPAs, dashboards, AI chat UI, 页面, 前端, 网页)' plus 'frontend AI' — matching what a user would actually say.

5 / 5

Distinctiveness Conflict Risk

Clear niche (Web/browser AI via @cloudbase/js-sdk) with explicit negative disambiguation — 'NOT for Node.js backend (use ai-model-nodejs), Mini Program (use ai-model-wechat), or image generation' — minimizing wrong-skill triggering.

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.

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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