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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)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations provide idempotentHint and destructiveHint. Description adds key-value scoping, persistence duration (24h for anonymous, persistent for authenticated), and pairing with other tools. No contradiction with 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?

Five sentences, no fluff. First sentence defines purpose, second gives usage context, third explains persistence, fourth mentions companion tools. Efficient and well-organized.

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 write tool, description covers purpose, usage, persistence, and partners. No output schema needed. Complete for 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.

Parameters4/5

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

Schema has 100% parameter description coverage. Description adds semantic examples like 'subject_property' and 'target_ticker', enhancing meaning beyond schema descriptions.

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?

Clearly states the tool saves data for later reuse, with specific examples (ticker, address, preference). Distinguishes from siblings like 'recall' and 'forget' by explicitly naming them as complementary 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?

Provides explicit 'when to use' guidance with concrete examples of what to store. Mentions pairing with recall and forget. Lacks explicit 'when not to use' but covers context well.

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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Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

The tool set mixes NASA-specific tools with a large number of financial and prediction market tools, causing confusion. Within the non-NASA tools, there is significant overlap (e.g., multiple Polymarket analysis tools, several research tools with vague boundaries).

Naming Consistency3/5

Most tools use snake_case, but naming patterns are inconsistent: some start with verbs (search_collections, get_collection), others are noun phrases (entity_profile, deep_research). There is no uniform verb_noun convention across the set.

Tool Count2/5

With 33 tools, the count is high. Although it may be appropriate for the underlying domain (data/prediction markets), it is excessive for the server's stated NASA focus, where only 3 tools are relevant.

Completeness1/5

For a server named 'Nasa Cmr', the tool set is severely incomplete: only three tools cover NASA Earth science (search/granules/collections), lacking any support for missions, datasets, or advanced queries. The non-NASA tools are comprehensive but disconnected from the server name.