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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
Behavior5/5

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

Discloses key behaviors beyond annotations: scoped by identifier, persistent for authenticated users, 24-hour expiry for anonymous sessions. Annotations indicate idempotentHint=true (no contradiction) and no destructive effects. Description adds valuable context about lifetime and scoping.

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, each serves a purpose: purpose, usage scenario, storage details, pairing with other tools. Front-loaded with core action. No wasted words.

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?

For a simple key-value store with 2 parameters and no output schema, the description covers all critical aspects: what it stores, when to use, lifetime, and related tools. Fully adequate for an agent to select and invoke correctly.

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 coverage is 100% with both parameters described. Description adds example key formats and value type ('any text'), but no additional details beyond schema. Baseline 3 is appropriate as schema already does the heavy lifting.

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 the tool's purpose: 'Save data the agent will need to reuse later'. It specifies the resource (data), action (save), and context (across conversations/sessions). Examples and pairing with recall/forget distinguish it from sibling tools.

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 describes when to use ('when you discover something worth carrying forward') with concrete examples (ticker, address, preference). Mentions authentication vs. anonymous session persistence but does not provide explicit when-not scenarios or alternatives beyond sibling names.

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

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_grounded, and deep_research all answering questions, and bet_research overlapping with polymarket_edges/arbitrage. The diverse tool set lacks clear boundaries.

Naming Consistency3/5

All names use snake_case, but verb patterns are inconsistent: some start with verbs (ask_pipeworx, remember) while others start with nouns (polymarket_arbitrage, entity_profile). Names vary widely in length and descriptiveness.

Tool Count2/5

33 tools is excessive for a server named 'Omdb', which implies a movie database. Most tools are unrelated to movies, indicating poor scoping for the server's purpose.

Completeness2/5

For the OMDb domain, only search and retrieval tools exist, with no create/update/delete operations. Overall, the tool set feels like a random collection with significant gaps relative to any coherent domain.