SKILLEMALL.ai

CD anyshare-mcp-skills

AnyShare 智能知识管理技能。支持:搜索文件、上传/下载文件、分享链接读取、全文写作(生成大纲→确认→写正文)。触发词:AnyShare、asmcp、文档库、文件管理、知识库、anyshare.aishu.cn 分享链接。

ClawHub Agent Skills author: Jerry v0.2.8 MIT-0 6 files body ≈ 4 191 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
C
72/100
safety, quality, tests
Safety 60%
100
Quality 40%
30
Run on models
none yet
Process rating
D
44/100
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error name-missing SKILL.md: frontmatter has no `name`
  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Implicit keys need to be on a single line at line 9, column 1: > **首次使用本技能时,按本文件「首次配置」章节执行。** ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 44/100

  • 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
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 70Execution cost. Instruction body is 4191 tokens
  • 100Steps. 15 steps
  • 100Consistency. Name and required fields are in place
  • 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 114: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -218 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 15 items
  • +4Has examples (17 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 30.

External checks

ClawHub: suspicious
The skill is a legitimate AnyShare document-management integration, but its setup flow asks users to paste an access token into chat and stores that bearer token in local configuration.
LLM: suspicious (high) · VirusTotal: · 28 May 2026