SKILLEMALL.ai

BC sales-daily-article

销售干货与防骗科普日更流水线(免费版)— 两条内容线(销售干货 / 防骗防坑)的标题公式与正文骨架;合规红线清单(严格脱敏、不承诺收益、不踩人群、不碰敏感、时令一致);存盘并同步进个人文章全文库,1000 字左右。选题靠人工扫库避重(付费版配自动查重脚本),发布前靠人工逐项自检(付费版配一键脱敏自检脚本)。适合想做销售类、防骗类日更自媒体的作者。当用户说"写今天的销售文""来一篇防骗文""日更一篇"或定时任务触发时使用。

ClawHub Hermes author: meimei-shoulu v1.2.0 MIT-0 2 files body ≈ 1 062 tokens Open the sourceclawhub.ai analyzed 8 h ago

销售干货与防骗科普日更流水线(免费版)— 两条内容线(销售干货 / 防骗防坑)的标题公式与正文骨架;合规红线清单(严格脱敏、不承诺收益、不踩人群、不碰敏感、时令一致);存盘并同步进个人文章全文库,1000…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
60
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
For the model run — optional
  • 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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 9, column 17: description_en: Daily sales-content pipeline (free): two content lines, proven … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-long-hermes description is 212 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "display_name_en"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "description_zh"
  • note frontmatter-key unknown frontmatter key "description_en"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 15 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1062 tokens
  • 100Running it twice. No mutating operations

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -220 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 212: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 15 items
  • +4Has examples (6 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: clean
This skill is a disclosed Chinese article-writing workflow that reads and updates a user-chosen local article library, with no evidence of hidden network access, credential use, destructive behavior, or deception.
LLM: benign (high) · VirusTotal: · 18 Sept 2026