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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations indicate idempotentHint=true; description adds key-value scoping by identifier, persistence details (24h for anonymous). Could mention overwrite behavior for existing keys but overall adds good context beyond annotations.

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 sentences, front-loaded with purpose, then usage, then technical details. No redundancy or filler.

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?

Simple tool with no output schema. Description covers purpose, usage, persistence, and sibling tools. Fully sufficient given annotations and schema.

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 covers 100% of parameters. Description adds usage examples for key (e.g., 'subject_property') and clarifies value is any text. Adds meaning beyond schema definitions.

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?

Clear verb+resource: 'Save data...reuse later'. Provides concrete examples (ticker, address, preference) and distinguishes from siblings recall/forget.

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?

Explicitly states when to use ('discover something worth carrying forward') and pairs with recall/forget. Mentions scoping and persistence but lacks explicit when-not-to-use guidance.

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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TDQS

A3.8/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, though there is some overlap between `ai_visibility_check` and `scan_competitor_ai_presence`, and between `bet_research` and `polymarket_edges`. Overall, an agent can distinguish them.

Naming Consistency3/5

Tool names follow snake_case but vary in prefix usage (e.g., `pipeworx_*`, `polymarket_*`, no prefix) and verb presence (e.g., `discover_tools` vs. `generate_llms_txt`). The pattern is readable but inconsistent.

Tool Count2/5

With 24 tools, the server is overloaded for the 'Prayer Times' name. Many tools are unrelated to prayer, suggesting poor scoping relative to the server's implied purpose.

Completeness2/5

For prayer times, the server includes core tools but lacks features like multi-day forecasts or advanced settings. However, the inclusion of many unrelated tools makes the set incoherent and incomplete for any single domain.