BF aws-wechat-article-writing
公众号写稿｜长文写作｜文章润色｜改写续写 — 公众号长文 AI 写作，从话题或提纲生成完整初稿，支持改写、续写、润色、开头结尾优化，可调 DeepSeek / GPT / Claude 或由 Agent 代写。面向自媒体作者、公众号运营、品牌文案。触发词（**单独触发仅限对已有稿子的修改**）：「改写」「润色」「续写」「续一段」「往下写」「接着这段写」「重写开头」「改结尾」「调整语气」「这段润色下」「把这段改活泼点」「优化用词」「用 GPT 重写」「用 DeepSeek 重写」。新写一篇请走 aws-wechat-article-main（main 内部会调用本 skill 生成初稿）；需要多环节串联（写+审+排+配图+发）也走 main。
公众号写稿｜长文写作｜文章润色｜改写续写 — 公众号长文 AI 写作，从话题或提纲生成完整初稿，支持改写、续写、润色、开头结尾优化，可调 DeepSeek / GPT / Claude 或由 Agent…
As a process F 38/100 · 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: 0. 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-publish/SKILL.md - warning
missing-refreference to a missing file: placeholder - warning
missing-refreference to a missing file: references/structure-template.md - warning
missing-refreference to a missing file: ../aws-wechat-article-review/SKILL.md - warning
missing-refreference to a missing file: references/usage.md - warning
missing-refreference to a missing file: ../aws-wechat-article-assets/SKILL.md - warning
missing-refreference to a missing file: ../aws-wechat-article-formatting/SKILL.md - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "url"
Process rating: all ten parameters 38/100
- 0Tools and files. 10 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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 28 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 60 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3508 tokens
- low The response is described with custom markup (4 tags): a typed call is more reliable
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
- -212 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 324: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 60 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.