Skip to main content
Glama

list_pipeline_recipes

Find pre-built compound hazard and multi-spectral pipeline recipes. Get a catalog with names, descriptions, categories, and step counts.

Instructions

List available pre-built compound hazard and multi-spectral pipeline recipes.

Returns: JSON string cataloging recipe names, descriptions, categories, and step counts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden and does disclose the primary behavior ('List') and the return format ('JSON string cataloging...'). However, it does not explicitly address side effects, authentication needs, or whether the list is static or dynamic—though 'List' implies read-only, it is not stated.

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?

Two short sentences with no filler. The core purpose is front-loaded, and the return format is given in a clearly separated second sentence. Every word earns its place.

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?

For a simple 0-parameter listing tool with an output schema, the description is nearly complete: it names the resource and specifies the JSON return contents. The only contextual gap is not pointing agents to describe_pipeline_recipe for recipe-level details, which would help navigation among sibling tools.

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?

The tool takes 0 parameters, so parameter semantics are trivially covered by the empty input schema. The baseline of 4 for 0-parameter tools applies; the description adds no parameter information, but none is needed.

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?

The description uses a specific verb ('List') and a specific resource ('pre-built compound hazard and multi-spectral pipeline recipes'), making it immediately distinct from siblings like run_pipeline or describe_pipeline_recipe. It also states the return content, reinforcing what the tool is for.

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

Usage Guidelines2/5

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

No guidance is provided on when to choose this tool over alternatives such as describe_pipeline_recipe (for details on a specific recipe) or list_supported_collections (for datasets). The description implies a browsing use case but never states exclusions or conditions.

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