BF aws-wechat-article-publish
公众号发布｜公众号草稿箱｜公众号群发｜图文推送｜微信 API｜wechat automation｜WeChat API automation｜auto publish｜scheduled publish — 公众号 API 发布工具，图文入草稿箱或直接群发，支持封面素材上传、发布前检查与 draft/published 模式切换。面向公众号运营、自动化内容团队、开发者。触发词：「发布」「提交」「群发」「推送」「发出去」「上传到公众号」「发到公众号」「可以发了吗」「发布前检查」。需要多环节串联（写+审+排+配图+发）请走 aws-wechat-article-main。
As a process F 33/100 · Will not run — References files that are not bundled: ../aws-wechat-article-main/SKILL.md, ../aws-wechat-article-main/references/first-time-setup.md, ../aws-wechat-article-main/references/articlescreening-schema.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: ../aws-wechat-article-main/SKILL.md - warning
missing-refreference to a missing file: ../aws-wechat-article-main/references/first-time-setup.md - warning
missing-refreference to a missing file: ../aws-wechat-article-main/references/articlescreening-schema.md - warning
missing-refreference to a missing file: ../aws-wechat-article-writing/SKILL.md - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "url"
Process rating: all ten parameters 33/100
- 0Tools and files. 4 referenced file(s) missing: ../aws-wechat-article-main/SKILL.md, ../aws-wechat-article-main/references/first-time-setup.md, ../aws-wechat-article-main/references/articlescreening-schema.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 46 mutating operations with no state check
- 100Steps. 28 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2062 tokens
- low 10 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 287: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 28 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (3 of 4)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.