SKILLEMALL.ai

BD 公众号历史文章库

查公众号历史文章与今日发文。给一个文章链接或 gh_ 原始ID,列出该号发过的文章(标题/时间/链接),支持翻页;也可只看今天发了什么。运营追号、竞品内容盘点常用。 适用场景:用户想看某个公众号发过哪些文章、最近更新、今日发文、按关键词翻历史时使用。

ClawHub Agent Skills author: dunkong v1.0.1 MIT-0 5 files body ≈ 646 tokens Open the sourceclawhub.ai analyzed 3 d ago

查公众号历史文章与今日发文。给一个文章链接或 gh 原始ID,列出该号发过的文章(标题/时间/链接),支持翻页;也可只看今天发了什么。运营追号、竞品内容盘点常用。 适用场景:用户想看某个公众号发过哪些文章、最近更新、今日发文、按关键词翻历史时使用。

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
D
41/100
Unfinished process
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.
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"

Process rating: all ten parameters 41/100

  • 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
  • 40Consistency. Frontmatter name (公众号历史文章库) differs from the folder (wechat-official-history)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 14 steps
  • 100Execution cost. Instruction body is 646 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

  • +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 125: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (4 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
The skill mostly matches a WeChat article lookup tool, but it also ships under-disclosed local-file upload capability, broad unused API metadata, and Python bytecode that warrant review before installing.
LLM: suspicious (high) · 4 Sept 2026