Skip to main content
Glama

ReefAPI

by io.github.reefapi

get_action_schema

Read-onlyIdempotent

FULL detail for ONE engine action: every parameter (type, required, description, allowed_values dropdown, default, example, min/max), what it returns, pricing, and a ready-to-run example_params. Call this right before call_engine so you send valid params — invalid enum values are rejected with the allowed list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesThe action's name on that engine (from get_engine_schema, e.g. 'search'). Returns the full param detail (type, required, allowed_values, default, example, min/max), what it returns, pricing, and ready-to-run example_params.
engineYesThe engine's name (e.g. 'zillow'), as returned by search_engines or get_catalog.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, idempotentHint, openWorldHint. The description adds that it returns parameter details, pricing, and example_params, enriching the behavioral understanding beyond annotations. No contradictions.

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?

Single paragraph, front-loaded with key information, no redundant sentences. Every sentence adds value.

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

Completeness5/5

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

Given no output schema, the description thoroughly explains what is returned (param detail, return, pricing, example_params). Combined with high schema coverage and annotations, the tool is fully contextualized for an AI agent.

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%, but the description adds context: action comes from get_engine_schema, engine from search_engines or get_catalog. This provides useful semantic linkage beyond 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?

The description clearly states it returns 'FULL detail for ONE engine action' and enumerates included items (parameters, return, pricing, example_params). It distinguishes itself from siblings like get_engine_schema (which lists all actions) and call_engine (which executes).

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

Usage Guidelines5/5

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

Explicitly instructs 'Call this right before call_engine so you send valid params' and warns about invalid enum rejection, providing clear context for when to use the tool.

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

All ReefAPI toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: search_engines for keyword-based discovery, get_catalog for a full list, get_engine_schema for action overview, get_action_schema for detailed parameters, and call_engine for execution. No overlap.

Naming Consistency5/5

Consistent snake_case with verb_noun pattern: search_*, get_catalog, get_*schema, call_engine. All follow a predictable structure.

Tool Count5/5

5 tools is well-scoped for an API discovery and invocation workflow. It covers search, exploration, and execution without being excessive or insufficient.

Completeness5/5

The tool surface covers the full lifecycle: engine discovery (search_engines, get_catalog), action schema (get_engine_schema, get_action_schema), and execution (call_engine). No obvious gaps.

Resources