SKILLEMALL.ai

BF linkfox-expert-amazon-single-competitor-analysis

专注对单个亚马逊 ASIN 进行全方位数据驱动的深度拆解,通过四步流水线整合 Keepa、Sorftime 与 SIF 数据,输出涵盖价格、BSR、评论、Deal、流量结构和生命周期等维度的 11 章节 HTML 深度报告。

ClawHub Agent Skills author: linkfox-ai v1.0.0 MIT-0 42 files body ≈ 746 tokens Open the sourceclawhub.ai analyzed 2 d ago

专注对单个亚马逊 ASIN 进行全方位数据驱动的深度拆解,通过四步流水线整合 Keepa、Sorftime 与 SIF 数据,输出涵盖价格、BSR、评论、Deal、流量结构和生命周期等维度的 11 章节 HTML 深度报告。

As a process F 35/100 · Will not run — References files that are not bundled: references/steps/S1.md, scripts/step_3_analyze.py, references/analysis-layouts.md

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
100
Quality 40%
52
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/steps/S1.md, scripts/step_3_analyze.py, references/analysis-layouts.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: 2. 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/steps/S1.md
  • warning missing-ref reference to a missing file: scripts/step_3_analyze.py
  • warning missing-ref reference to a missing file: references/analysis-layouts.md
  • warning missing-ref reference to a missing file: references/api.md
  • note frontmatter-key unknown frontmatter key "zh_name"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/steps/S1.md, scripts/step_3_analyze.py, references/analysis-layouts.md
  • 0Tools and files. 4 referenced file(s) missing: references/steps/S1.md, scripts/step_3_analyze.py, references/analysis-layouts.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. 24 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 746 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 112: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 24 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 52.

External checks

ClawHub: suspicious
The skill does the advertised Amazon competitor analysis, but it also includes account login, billing, public upload, and telemetry behaviors that need manual review before installation.
LLM: suspicious (high) · 21 Aug 2026