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boltwork-mcp

boltwork-mcp

by Squidboy30
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

analyse_image

Analyse an image from a URL to extract content type, objects, visible text, dominant colors, sentiment, and tags. Costs 200 sats via Lightning.

Instructions

Analyse an image from a URL. Returns structured description including content type, objects detected, any visible text (OCR), dominant colors, sentiment, and tags. Costs 200 sats via Lightning. Supported formats: JPEG, PNG, GIF, WebP.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "analyse_image"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesURL of the image to analyse
detailNoAnalysis detail level: low, high, or auto (default: auto)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.22

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided; the description discloses the cost (200 sats via Lightning) and supported formats, and lists the return fields. It does not mention side effects or rate limits, but as a read-only analysis, this is acceptable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (two sentences plus a list) and well-structured, with no extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description covers key aspects: inputs, outputs, cost, and formats. It lacks details on error handling or size limits, but is sufficient for an agent to use the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with both parameters described; the description adds value by explaining the detail parameter's options and noting the cost and formats, which are not in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool analyzes an image from a URL, lists specific outputs (content type, objects, OCR, colors, sentiment, tags) and supported formats, distinguishing it from sibling analysis tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description indicates explicit use case (image analysis) and mentions cost and supported formats, but lacks explicit when-not-to-use guidance or comparison with alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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