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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. Also covers multimodal image input (image_url content blocks, OCR and form extraction) — vision-capable models only. Models via wx.cloud.extend.AI.createModel with groups cloudbase (main managed, also 小程序成长计划 with `hy4-preview` / `hy3` / `deepseek-v4.1-flash`), the legacy hunyuan-v3 / hunyuan-exp, or custom-*; model id goes in the `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).

Quality

89%

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%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 delivers exceptional actionability and a rigorously validated preflight workflow with real feedback loops, all grounded in executable code. Its weaknesses are redundancy (createModel rules and preflight prerequisites stated three times) and the absence of any progressive disclosure — everything, including type definitions and the multimodal guide, lives inline in one long file.

Suggestions

Consolidate the createModel legality rules into one authoritative section (the STOP table) and have 'Available Providers and Models' and Best Practice #2 reference it instead of restating the four values and the wrong-examples list.

Move the Type Definitions, the JS/Node vs Mini Program API comparison table, and the multimodal three-rules deep-dive into reference files (e.g. references/types.md, references/multimodal.md) linked one level deep from SKILL.md.

Replace the prerequisite blockquote repeated verbatim under generateText, streamText, and Error Handling with a single one-line pointer back to the preflight section.

DimensionReasoningScore

Conciseness

Mostly dense with high-value, non-obvious specifics, but noticeably repetitive: the four legal createModel values are stated in full in the STOP section, again in "Available Providers and Models" ("Only the four kinds of values below are legal"), and again in Best Practice #2, and the preflight prerequisite blockquote is repeated under generateText, streamText, and Error Handling. Anchor 3 ("could be tightened") fits better than 2 because the redundancy targets a documented agent failure mode rather than padding with known concepts.

3 / 5

Actionability

Fully executable, copy-paste-ready code throughout: callCloudApi payloads with exact PascalCase params for DescribeActivityInfo / DescribeEnvPostpayPackage / DescribeAIModels / UpdateAIModel / CreateAIModel, complete generateText / streamText / multimodal examples, custom-onboarding registration, and TypeScript type definitions. Hit criteria and miss-handling (purchase links, enrollment URL) are concrete.

5 / 5

Workflow Clarity

The "Mandatory Two-Step Preflight" gives a fixed ordered sequence (① eligibility → ② group readiness) with explicit validation checkpoints (hit criteria for both billing checks, group readiness = GroupName exists + Status===1 + Model present), feedback loops ("if you hit InvalidParameter, switch casing and retry"; keep the draft on JSON parse failure and let the user retry), and a self-verification checklist in Best Practice #13 (run in DevTools, confirm onText chunks, [DONE] termination, no console errors).

5 / 5

Progressive Disclosure

Section headers are clear and well-ordered, but with no bundle files the entire ~550-line body is a monolith: the Type Definitions, the API comparison table, and the multimodal three-rules deep-dive are classic reference-file material inlined in SKILL.md. Anchor 3 ("content that should be separate is inline") fits — structure exists, but the split is missing; not anchor 2 since navigation via headers is good and nothing is buried.

3 / 5

Total

16

/

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.

The description is a model example: concrete capabilities, bilingual trigger terms, explicit use and do-not-use guidance, and clear redirects to sibling skills for adjacent environments. Dense with specifics without fluff or over-claims.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Covers generateText and streamText with callbacks (onText, onEvent, onFinish)", "multimodal image input (image_url content blocks, OCR and form extraction)", model selection via createModel with named groups — with comprehensive coverage of the skill's surface. No vague or abstract language; even API contract details ("streamText needs a data wrapper, generateText returns the raw response") are stated.

5 / 5

Completeness

Explicitly answers what ("Covers generateText and streamText... multimodal image input... Models via wx.cloud.extend.AI.createModel") and when ("Use this skill for WeChat Mini Program AI via wx.cloud.extend.AI"), with concrete negative triggers ("NOT for browser/Web (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation"). Both halves are explicit and specific.

5 / 5

Trigger Term Quality

Natural terms users would say are covered in both English and Chinese: "WeChat Mini Program", "小程序", "wx.cloud", "OCR", "form extraction", plus concrete API and model names (streamText, generateText, hy4-preview, hy3, deepseek-v4.1-flash, hunyuan-v3). Includes synonyms and both language variants of the platform name.

5 / 5

Distinctiveness Conflict Risk

Clear niche — WeChat Mini Program client AI calls via wx.cloud.extend.AI — and it explicitly redirects overlapping intents to sibling skills (ai-model-web, ai-model-nodejs, http-api-cloudbase), minimizing wrong-skill triggering. Scope boundaries are named rather than implied.

5 / 5

Total

20

/

20

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.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (557 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository

TencentCloudBase/CloudBase-AI-Toolkit

Path

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

Reviewed

Table of Contents

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