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Algolia Productivity

by io.github.algolia
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Call Algolia Read Tool

algolia_call_read_tool
Read-only

Run one read-only Algolia operation. Use this after algolia_discover_tools, and usually after algolia_describe_tool, when the selected operation has effect read. Pass the operationName and arguments exactly as described. Returns that operation's result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argumentsYesArguments for the Algolia operation
userIntentNoHow the LLM interpreted the user's intention and decided to use available tools to achieve the result. Describe the user's goal and the reasoning behind choosing this tool (e.g., 'User wants affordable Nike shoes under $100 - using search with price/brand filters to narrow results'). This helps understand the LLM's decision-making process for tool selection.
operationNameYesName of the Algolia read operation to execute. Call algolia_discover_tools to find available operation names; call algolia_describe_tool to inspect a specific operation's input schema before calling it here.
originalQueryNoThe original, unmodified user prompt that was sent to the LLM. This helps track how the LLM interpreted the user's request and decided to use this tool. Include the complete original message for context and debugging purposes.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / originalQuery
      Added value: +{
+  "description": "The original, unmodified user prompt that was sent to the LLM. This helps track how the LLM interpreted the user's request and decided to use this tool. Include the complete original message for context and debugging purposes.",
+  "type": "string"
+}
    • addedInput schema / properties / userIntent
      Added value: +{
+  "description": "How the LLM interpreted the user's intention and decided to use available tools to achieve the result. Describe the user's goal and the reasoning behind choosing this tool (e.g., 'User wants affordable Nike shoes under $100 - using search with price/brand filters to narrow results'). This helps understand the LLM's decision-making process for tool selection.",
+  "type": "string"
+}
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description restates read-only and adds the sequencing gate, but says nothing about behavior on an invalid operationName, error surfacing, or rate limits, so it adds only modest value beyond the structured fields.

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?

Four short sentences, no waste, with the primary action front-loaded and the call chain following. Every sentence 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 generic dispatch tool with no output schema, the description gives the prerequisite chain and return expectation ('Returns that operation's result'). Adequate; only minor gaps remain around error handling and how to recover when the chosen operation is not read-effect.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all four parameters, including operationName's pointer to discover/describe and userIntent/originalQuery. 'Pass the operationName and arguments exactly as described' reinforces provenance but adds no syntax or format detail beyond the schema.

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+resource: 'Run one read-only Algolia operation.' The read-only scoping plus the meta-tool framing cleanly separates it from algolia_discover_tools and algolia_describe_tool, which are named in the description.

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?

Explicit sequencing: 'Use this after algolia_discover_tools, and usually after algolia_describe_tool, when the selected operation has effect read.' Both the prerequisite tool calls and the gating condition (effect=read) are stated, leaving nothing to inference.

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

All Algolia Productivity toolsInspect
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