SKILLEMALL.ai

BF linkfox-ecommerce-compliance-detection

电商知识产权与合规检测一站式 AI 工具集,整合睿观知产合规检测(版权/商标/外观专利/实用新型专利/图片政策)与智慧芽专利数据查询(著录/权利要求/说明书/附图/法律状态/家族/引用/以图搜图/PDF)共 2 类底层工具、22 项子能力。

ClawHub Agent Skills author: linkfox-ai v1.2.3 MIT-0 49 files body ≈ 4 009 tokens Open the sourceclawhub.ai analyzed 26 h ago

电商知识产权与合规检测一站式 AI 工具集,整合睿观知产合规检测(版权/商标/外观专利/实用新型专利/图片政策)与智慧芽专利数据查询(著录/权利要求/说明书/附图/法律状态/家族/引用/以图搜图/PDF)共 2 类底层工具、22 项子能力。

As a process F 34/100 · Will not run — References files that are not bundled: scripts/upload_image.py, references/<子能力>.md

AnalyzerSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
100
Quality 40%
51
Run on models
none yet
Process rating
F
34/100
Will not run
References files that are not bundled: scripts/upload_image.py, references/<子能力>.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 frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 6, column 17: description_en: One-stop e-commerce IP & compliance detection AI toolkit integr… ^ ); 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")
  • warning missing-ref reference to a missing file: scripts/upload_image.py
  • warning missing-ref reference to a missing file: references/<子能力>.md
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "display_name_en"
  • note frontmatter-key unknown frontmatter key "description_zh"
  • note frontmatter-key unknown frontmatter key "description_en"

Process rating: all ten parameters 34/100

Will not run. References files that are not bundled: scripts/upload_image.py, references/<子能力>.md
  • 0Tools and files. 2 referenced file(s) missing: scripts/upload_image.py, references/<子能力>.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
  • 70Execution cost. Instruction body is 4009 tokens
  • 100Steps. 36 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. No mutating operations
  • low The response is described with custom markup (8 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
  • -31 of 12 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 120: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 36 items
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (23 of 23)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 51.

External checks

ClawHub: suspicious
The skill mostly matches its LinkFox compliance-checking purpose, but it needs Review because it sends credentials to environment-selected endpoints and may save full results outside the location it promises.
LLM: suspicious (high) · 14 Aug 2026