SKILLEMALL.ai

BF wechat-account-analyzer

公众号账号诊断工具是对任意公众号账号进行四维度量化评分(内容健康度、用户活跃度、内容核心数据、运营规范性),对标行业平均水平,输出可落地的运营优化建议。

ClawHub Agent Skills author: RedFox v1.0.3 MIT-0 13 files body ≈ 1 428 tokens Open the sourceclawhub.ai analyzed 26 h ago

公众号账号诊断工具是对任意公众号账号进行四维度量化评分(内容健康度、用户活跃度、内容核心数据、运营规范性),对标行业平均水平,输出可落地的运营优化建议。

As a process F 35/100 · Will not run — References files that are not bundled: references/core_workflow.md

AnalyzerSoftware developmentData and analyticsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/core_workflow.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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. The text references files that are not there: add them or drop the references.
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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/core_workflow.md

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/core_workflow.md
  • 0Tools and files. 1 referenced file(s) missing: references/core_workflow.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
  • 100Steps. 34 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1428 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)
  • +3Description length 76: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 30 headings
  • +3Step-by-step instructions: 34 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
The skill mostly performs the advertised WeChat account analysis, but it also handles credentials, writes raw data locally, and can create follow-up syncing tasks with insufficient boundaries.
LLM: suspicious (high) · 2 Sept 2026