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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?

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SecuritybySnyk

Passed

No findings from the security scan

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 outstanding actionability and a rigorously validated, fixed-order workflow that directly counters a documented agent hallucination (the createModel provider argument). Its weaknesses are repetition — the same rules are deliberately restated three or four times, inflating token cost — and a monolithic 557-line structure with no reference files to offload type definitions and model catalogs.

Suggestions

State the four legal createModel(provider) values once (in the STOP section) and have later sections and Best Practices reference it instead of fully restating it; likewise drop the repeated "no model is enabled by default" and the duplicated preflight blockquotes before each example.

Move the Type Definitions section, the managed-model catalog/pricing tables, and the Custom Onboarding walkthrough into a references/ file (e.g. references/models.md and references/custom-onboarding.md), keeping only a few key examples inline in SKILL.md.

Consolidate the preflight's per-branch guidance so each billing path's hit criterion and on-miss action appears exactly once, trimming the ~100-line eligibility table's duplicated model-selection advice.

DimensionReasoningScore

Conciseness

Everything is novel wx-specific knowledge rather than concepts Claude already knows, but the same facts are restated repeatedly: the four legal createModel values appear in full three times (STOP section, Available Providers, Best Practices #2), "no model is enabled by default" recurs 4+ times, and the preflight prerequisite blockquote is repeated before each code example. This is mostly efficient but visibly could be tightened, matching anchor 3 rather than anchor 4's "minor instances".

3 / 5

Actionability

All guidance is executable and copy-paste ready: complete callCloudApi payloads for DescribeActivityInfo/DescribeAIModels/UpdateAIModel/CreateAIModel, a working streamText example with the data wrapper and all three callbacks, the full chooseMedia→compressImage→uploadFile→getTempFileURL chain, and precise hit criteria ("postpayPackageId starts with pkg_tcb_tokencredits_, status ∉ [3, 4]"). Common cases (text, streaming, vision, custom onboarding, errors) are all covered with concrete code.

5 / 5

Workflow Clarity

The two-step preflight is a fixed-order sequence ("① eligibility → ② group readiness. Do not swap the two") with explicit validation hit criteria, on-miss branches (enrollment/purchase links, UpdateAIModel), an error-recovery loop ("if you hit InvalidParameter, switch casing and retry"), a numbered decision procedure, and a final self-verify checklist (Build → DevTools run → onText arrives → [DONE] terminates → no console errors). Database writes are gated by defensive parsing and user review, satisfying the validation expectations for DB operations.

5 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are absent) and all 557 lines live in SKILL.md, including ~70 lines of TypeScript type definitions, provider/pricing catalog tables, and a full custom-onboarding guide — reference material that belongs in separate files per the anchor-4 pattern. Section headers are clear (above anchor 2's "minimal structure"), but "content that should be separate is inline" with zero offload matches anchor 3, and the under-50-line simple-skill exception plainly does not apply.

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 exemplary: it states concrete capabilities with exact API names and behavioral gotchas (data wrapper, raw response), includes bilingual trigger terms and model ids, and explicitly delimits when to use it versus sibling skills. No fluff or over-claims despite its density.

DimensionReasoningScore

Specificity

Names multiple concrete actions with exact API surface — "generateText and streamText with callbacks (onText, onEvent, onFinish)", "multimodal image input (image_url content blocks, OCR and form extraction)", "createModel with groups cloudbase" — giving comprehensive coverage of the skill's domain with no gaps.

5 / 5

Completeness

Explicitly answers both questions: what ("Covers generateText and streamText… multimodal image input…") and when ("Use this skill for WeChat Mini Program AI via wx.cloud.extend.AI (小程序, wx.cloud apps)") with concrete trigger phrases and explicit negative triggers, matching the anchor-5 example.

5 / 5

Trigger Term Quality

Covers natural terms a user would say in both English and Chinese ("WeChat Mini Program AI", "小程序", "wx.cloud apps", "OCR and form extraction") plus concrete model ids ("hunyuan-v3", "deepseek-v4.1-flash"), matching the comprehensive-synonyms anchor rather than the merely-good anchor 4.

5 / 5

Distinctiveness Conflict Risk

Clear niche (wx.cloud.extend.AI in Mini Programs) with explicit routing away from siblings — "NOT for browser/Web (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation" — so conflict risk with related skills is minimal.

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

connectors/cloudbase-intl/skills/references/ai-model-wechat/SKILL.md

Reviewed

Table of Contents

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