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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?

The description adds meaningful behavioral context beyond the annotations: data is stored as a key-value pair scoped by identifier, and retention differs for authenticated (persistent) vs anonymous (24 hours). It does not contradict the idempotent or non-destructive hints, and while it doesn't discuss key overwrites, the provided context is sufficient.

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?

The description is three sentences, front-loaded with the primary action, and each sentence adds distinct value: what it does, when to use it, and companion tools. No filler or redundancy.

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 two-parameter key-value store with annotations and a fully described schema, the description covers usage context, persistence semantics, and companion tools. Since there is no output schema, no return-value documentation is needed, and the description is complete enough for an agent to invoke it 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 descriptions for both key and value, including example formats. The description reinforces the key-value pair concept and gives content examples, but this does not significantly add beyond what the schema already provides.

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 states 'Save data the agent will need to reuse later' with a specific verb and resource, clearly distinguishing it from sibling tools recall and forget by framing the action as saving (vs retrieving/deleting). It also gives concrete examples of what to store (ticker, address, preference).

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?

The description explicitly says 'Use when you discover something worth carrying forward' and then explains the persistence behavior (authenticated vs anonymous). It directly names companion tools: 'Pair with recall to retrieve later, forget to delete,' providing clear alternatives and when-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

A3.6/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, such as the four ask_pipeworx variants and several Polymarket analysis tools. While descriptions are detailed, the distinctions are nuanced, and an agent may struggle to select the correct tool without careful reading.

Naming Consistency3/5

Tool names mix styles: Kraken tools are short nouns (ticker, depth), while Pipeworx tools use various patterns (verb_noun, noun_noun). No single convention dominates, but names are generally readable and descriptive.

Tool Count2/5

40 tools is high, combining two distinct domains. Many tools serve overlapping purposes, making the set feel bloated. A more focused server or consolidation of similar tools would improve scope.

Completeness3/5

The Pipeworx data tools cover a broad range of retrieval and analysis, including prediction markets, memory, and subscriptions. However, the Kraken tools lack trading functionality, and there are redundant tools that could be merged.