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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.

The body is highly actionable and the two-step preflight workflow is a model of explicit sequencing, validation checkpoints, and feedback loops. Its weaknesses are systematic internal repetition of the same warnings and a monolithic 450-line structure with no progressive disclosure into reference files.

Suggestions

Consolidate the repeated createModel("vendor") warning (STOP section, 'Common Mini Program mistake' block, and Best Practice #2) into one authoritative statement and reference it from the other spots instead of restating it in full.

Split stable reference material into bundle files — e.g. references/types.md for the TypeScript interfaces, references/providers.md for the provider/model catalog and custom-onboarding walkthrough — keeping SKILL.md as a lean overview with one-level-deep, clearly signaled links.

State the 'for the resource pack branch, swap createModel(...) to cloudbase' caveat once (e.g. in the preflight section or a single note before the API sections) rather than repeating it before the generateText, streamText, and error-handling examples.

DimensionReasoningScore

Conciseness

The body contains no padding about concepts Claude already knows, but it repeats the same guidance multiple times: the createModel("vendor") warning appears in the STOP section, again in the "⚠️ Common Mini Program mistake" block, and again in Best Practice #2, and the "for the resource pack branch, swap to cloudbase" prerequisite note is restated before the generateText, streamText, and error-handling examples. This matches the anchor for mostly-efficient content that includes unnecessary explanation or could be tightened — more than the minor instances required for a 4.

3 / 5

Actionability

Fully executable throughout: complete callCloudApi snippets with concrete params, copy-paste-ready createModel/generateText/streamText code with all callbacks, explicit hit criteria (e.g. "postpayPackageId starts with pkg_tcb_tokencredits_"), on-miss purchase URLs, a full error-handling example, and TypeScript interfaces. This matches the anchor for copy-paste-ready guidance covering the common cases.

5 / 5

Workflow Clarity

The Mandatory Two-Step Preflight is a clearly sequenced workflow with a fixed order (① eligibility → ② group readiness), explicit hit/miss criteria per branch, a retry feedback loop ("if you hit InvalidParameter, switch casing and retry"), and a final self-verification step ("Self-verify before claiming done" with concrete checks a-c). This matches the anchor for clear sequencing with explicit validation steps and error-recovery feedback loops.

5 / 5

Progressive Disclosure

Section structure is good, but the ~450-line body is monolithic: the Type Definitions, the JS/Node comparison table, the Custom Onboarding walkthrough, and the provider catalog tables are all inlined in SKILL.md with no reference files at all (no references/, scripts/, or assets/ exist). This fits the anchor for content that should be in separate files being inline — short of a 4, which requires most content appropriately placed with mostly-clear references.

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.

An excellent description: concrete API-level capabilities, explicit positive and negative trigger guidance, and explicit disambiguation against sibling skills. The only gap is a handful of missing natural-language synonyms (chat, LLM, chatbot) that would round out trigger coverage.

DimensionReasoningScore

Specificity

The description lists multiple concrete, API-level actions: "Covers generateText and streamText with callbacks (onText, onEvent, onFinish); streamText needs a data wrapper, generateText returns the raw response" and "Models via wx.cloud.extend.AI.createModel with groups hunyuan-exp... cloudbase... or custom-*". This matches the anchor for multiple specific concrete actions with comprehensive coverage; no vague filler is present.

5 / 5

Completeness

It explicitly answers both what ("Covers generateText and streamText with callbacks..." plus model-group selection) and when ("Use this skill for WeChat Mini Program AI" plus explicit negative triggers "NOT for browser/Web (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation"). This matches the 5 anchor: both questions clearly and explicitly answered with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural triggers are well covered — "WeChat Mini Program AI", "小程序", "wx.cloud apps", "generateText", "streamText", "hunyuan-exp", "custom-*" — which a user with this need would plausibly say. It falls short of the 5 anchor because common conversational variants (e.g. "AI chat", "chatbot", "LLM", "streaming responses in Mini Program") are not included.

4 / 5

Distinctiveness Conflict Risk

The niche is unambiguous — the wx.cloud.extend.AI namespace and Mini Program context — and it explicitly redirects overlapping cases to sibling skills ("use ai-model-web", "use ai-model-nodejs"), minimizing conflict risk. This is the clear-niche anchor with minimal conflict.

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

config/.claude/skills/ai-model-wechat/SKILL.md

Reviewed

Table of Contents

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