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by yaniswav
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_image

Read-onlyIdempotent

Fetch a single live frame from a ROS2 Image or CompressedImage topic as image content plus JSON metadata, with optional max-edge resizing for raw frames.

Instructions

One live frame as image content plus JSON metadata. CompressedImage passes through; raw needs topicforge[image]. Needs the sampling helper. Big best-effort frames can drop. Mock: a fixed gradient.

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": {
      "topic": "<topic>"
    },
    "name": "get_image"
  }
}

Input Schema

NameRequiredDescriptionDefault
topicYesA sensor_msgs/Image or CompressedImage topic.
max_edgeNoLongest edge of a raw image.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.10.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safe-read profile (readOnly, idempotent, non-destructive), and the description adds genuinely new behavioral facts: raw images require the `topicforge[image]` extra, a sampling helper is required, large best-effort frames may be dropped, and mock mode returns a fixed gradient. The 'needs the sampling helper' phrase is underspecified, which keeps it from a 5.

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

Conciseness4/5

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

Very short and front-loaded: the return shape comes first, then encoding handling, then prerequisites and failure modes. The telegraphic fragments are efficient but occasionally ambiguous, e.g. which 'sampling helper' is meant.

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?

With no output schema, the description does the necessary work by stating the return is image content plus JSON metadata. Dependencies and degradation are covered; what's missing is error behavior for a non-image topic and whether max_edge affects compressed frames.

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%, so the baseline is 3; the description earns a bump by explaining how the `topic` parameter behaves — CompressedImage passes through unchanged while raw Image needs an optional dependency. `max_edge` is left to the schema, whose own description is adequate.

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

Purpose4/5

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

States a specific verb and resource: fetch one live frame from a topic, returned as image content plus JSON metadata. That clearly separates it from listing/introspection siblings. It doesn't name any alternative tool explicitly, so it stops just short of 5.

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

Usage Guidelines3/5

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

Usage is implied by 'one live frame' — you call it when you want a single image rather than a stream or sample list — and the caveat about big best-effort frames dropping hints at limits. There is no explicit when-not guidance and no named alternative for related needs (e.g. sampling many messages).

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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