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ai-model-wechat

Use this skill for WeChat Mini Program AI via wx.cloud.extend.AI (小程序, wx.cloud apps). Covers generateText and streamText with callbacks (onText, onEvent, onFinish); streamText needs a data wrapper, generateText returns the raw response. Models via wx.cloud.extend.AI.createModel with groups hunyuan-exp (小程序成长计划), cloudbase (main managed), or custom-*; model id goes in the data wrapper `model` field. MUST run two-step preflight before code — see body. NOT for browser/Web (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation (use ai-model-nodejs).

69

Quality

87%

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-wechat in TencentCloudBase/CloudBase-AI-Toolkit

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.

An exceptionally actionable, well-sequenced body whose workflows carry explicit validation and error-recovery checkpoints. Its weaknesses are redundancy (the createModel warning and preflight prerequisites are each repeated multiple times) and a monolithic layout that inlines API-reference material a separate file should hold.

Suggestions

State the createModel misuse warning once (in the STOP section) and cross-reference it from section B and Best Practice #2 instead of repeating the full wrong/right examples three times.

Remove the repeated 'Prerequisite: the Mandatory Two-Step Preflight has been completed' blocks before each code example and state the dependency once near the preflight section.

Move the tcb API reference (CreateAIModel/UpdateAIModel/DescribeAIModels parameter details and the TypeScript type definitions) into a references/ file linked one level deep from SKILL.md, keeping only the decision logic and key examples inline.

DimensionReasoningScore

Conciseness

Mostly efficient because the bulk is non-inferable API detail (billing actions, GroupName rules, hit/miss criteria), but the createModel misuse warning is repeated three times (STOP section, section B note, Best Practice #2), the 'two-step preflight' prerequisite block is restated before three separate examples, and the WxGenerateTextResponse interface re-documents the standard OpenAI chat-completion shape Claude already knows.

3 / 5

Actionability

Fully executable guidance throughout: exact callCloudApi params for each tcb action, explicit hit criteria and on-miss handling with purchase/enrollment URLs, copy-paste wx.cloud generateText/streamText examples, and a concrete decision procedure for user-named models.

5 / 5

Workflow Clarity

The mandatory two-step preflight is clearly sequenced in fixed order (① billing eligibility → ② group readiness) with explicit validation checkpoints (hit criteria per billing path, group readiness = GroupName + Status === 1 + model present), error-recovery loops (InvalidParameter casing retry, ModelNotEnabled guidance), and a self-verify checklist (run in DevTools, confirm onText chunks, [DONE] termination, clean console).

5 / 5

Progressive Disclosure

The body is well-structured with clear section headers, but it is a single monolithic ~440-line file with no bundle references — the tcb API reference (CreateAIModel/UpdateAIModel/DescribeAIModels params), type definitions, and SDK comparison table are all inlined rather than split into one-level-deep reference files.

3 / 5

Total

16

/

20

Passed

Description

92%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 specific, complete, and highly distinguishable description: it names the exact SDK surface, both call semantics, the three provider groups, and an explicit use/don't-use boundary with sibling routing. Only minor gap is a handful of missing natural trigger synonyms.

DimensionReasoningScore

Specificity

The description lists multiple concrete capabilities — 'generateText and streamText with callbacks (onText, onEvent, onFinish)', 'streamText needs a data wrapper, generateText returns the raw response', and the three legal createModel groups — with comprehensive, non-generic coverage of the skill's scope.

5 / 5

Completeness

It explicitly answers both 'what' (both SDK calls with their exact semantics and the createModel group rules) and 'when' ('Use this skill for WeChat Mini Program AI via wx.cloud.extend.AI… NOT for browser/Web… Node.js backend… image generation'), with concrete trigger phrases and sibling-skill routing.

5 / 5

Trigger Term Quality

Good keyword coverage including natural synonyms ('WeChat Mini Program', '小程序', 'wx.cloud', 'hunyuan', 'generateText', 'streamText'), but a few natural phrasings users would say are absent (e.g. '微信小程序', 'miniprogram', plain 'streaming AI').

4 / 5

Distinctiveness Conflict Risk

Clear niche (WeChat Mini Program wx.cloud.extend.AI) with an explicit NOT-for list delegating browser/Web to ai-model-web and Node.js/image-generation to ai-model-nodejs, giving minimal conflict risk with sibling skills.

5 / 5

Total

19

/

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

plugin/cloudbase/skills/ai-model-wechat/SKILL.md

Reviewed

Table of Contents

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