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ai-model-wechat

Use this skill for WeChat Mini Program AI via wx.cloud.extend.AI (小程序, 企业微信小程序, wx.cloud apps). Features generateText and streamText with callbacks (onText, onEvent, onFinish). Models via wx.cloud.extend.AI.createModel with groups hunyuan-exp (小程序成长计划), cloudbase (main managed), or custom-*. Model IDs (deepseek-v4-flash, deepseek-v3.2, hunyuan-2.0-instruct-20251111, glm-5, kimi-k2.6) go in the data wrapper model field. API differs from JS/Node SDK — streamText needs data wrapper, generateText returns raw response. MUST run two-step preflight before code — see body. Keywords: Mini Program AI, wx.cloud.extend.AI, 小程序成长计划, ai_miniprogram_inspire_plan, Token Credits 资源包, generateText, streamText, createModel, hunyuan-exp, TokenHub, Hunyuan, DeepSeek, GLM, Kimi, MiniMax. NOT for browser/Web (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation (use ai-model-nodejs).

71

Quality

88%

Does it follow best practices?

Run evals on this skill

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-wechat 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 with an excellently sequenced, validated two-step workflow, but it is verbose from purposeful repetition and monolithic with no reference files to offload the API/type/catalog detail. Splitting the type definitions and callCloudApi payloads into a reference file would improve both conciseness and progressive disclosure.

Suggestions

Extract the TypeScript type definitions and the callCloudApi payload examples into a references/ file (e.g. references/api.md) and link to it one level deep, reducing inline bulk and improving progressive_disclosure.

Consolidate the recurring createModel warning ('no model enabled by default', the three legal values, the hunyuan-exp↔cloudbase swap) into a single authoritative section and cross-reference it instead of restating it in the STOP section, providers section, and best practices.

Move the per-section 'swap to cloudbase + UpdateAIModel' prerequisite notes into one canonical preflight reference rather than repeating the caveat before generateText, streamText, and error-handling examples.

DimensionReasoningScore

Conciseness

Dense with genuinely non-obvious, environment-specific knowledge and no basic-concept filler, but the createModel warning, the 'no model enabled by default' point, and the 'swap hunyuan-exp↔cloudbase' prerequisite recur across the STOP section, providers section, and best practices — mostly efficient with some tightening possible.

2 / 3

Actionability

Copy-paste-ready callCloudApi blocks with exact params, executable generateText/streamText code with named callbacks, exact TypeScript interfaces, and a decision tree with explicit hit/miss criteria — fully executable and specific.

3 / 3

Workflow Clarity

The two-step preflight is rigidly sequenced (eligibility → group readiness) with explicit validation checkpoints (DescribeAIModels → DescribeManagedAIModelList → UpdateAIModel) and a self-verify feedback loop in best practice #13, matching the clear-sequence-with-validation anchor.

3 / 3

Progressive Disclosure

No bundle files exist (references/scripts/assets absent), and the ~440-line body keeps callCloudApi payloads, type definitions, the model catalog, and the API-comparison table inline rather than split into one-level-deep reference files — structure exists via clear headers but it is largely a single-file dump.

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 specific, well-triggered, complete, and clearly distinct from sibling skills, with concrete actions and natural bilingual keywords. It is longer than ideal but every clause carries information rather than fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete actions and named primitives — generateText/streamText with onText/onEvent/onFinish callbacks, createModel with three named groups (hunyuan-exp, cloudbase, custom-*), specific model IDs, the data-wrapper requirement, and a mandatory two-step preflight — matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly answers both what ('Features generateText and streamText...') and when ('Use this skill for...', plus a 'NOT for...' boundary), matching the 'clearly answers both what AND when with explicit triggers' anchor.

3 / 3

Trigger Term Quality

Good bilingual coverage of terms users naturally say ('WeChat Mini Program AI', '小程序', '小程序成长计划', 'Hunyuan', 'DeepSeek', 'GLM', 'Kimi', 'MiniMax'), matching the 'good coverage of natural terms' anchor.

3 / 3

Distinctiveness Conflict Risk

A clear niche (WeChat Mini Program AI via wx.cloud.extend.AI) with explicit disambiguation against sibling skills (ai-model-web, ai-model-nodejs), making it unlikely to trigger for the wrong skill.

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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