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BD amazon

通过官方 Gecho Bridge MCP 搜索 Amazon 商品、获取已知商品详情并采集商品评论。适用于市场发现、商品库调研、商品比较、评论分析和 ASIN 级研究。

ClawHub Hermes author: Gecho AI v1.1.37 MIT-0 3 files body ≈ 2 366 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

通过官方 Gecho Bridge MCP 搜索 Amazon 商品、获取已知商品详情并采集商品评论。适用于市场发现、商品库调研、商品比较、评论分析和 ASIN 级研究。

As a process D 38/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
D
38/100
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.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 85 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill

Process rating: all ten parameters 38/100

  • 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
  • 0Consistency. Frontmatter name (amazon) differs from the folder (amazon-zh-cn)
  • 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
  • 100Steps. 103 steps
  • 100Execution cost. Instruction body is 2366 tokens
  • 100Running it twice. No mutating operations
  • low 18 top-level sections: this looks like several domains in one skill

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 85: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 103 items
  • +4Has examples (8 code blocks)

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

External checks

ClawHub: clean
This skill is a disclosed Amazon research helper that routes user-requested product and review lookups through Gecho, with no evidence of hidden or destructive behavior.
LLM: benign (high) · VirusTotal: · 22 Aug 2026