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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

A4.7/5.0
Behavior4/5

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

Annotations provide readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds extra behavioral context by explaining 'Stored as a key-value pair scoped by your identifier' and that 'Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours.' This goes beyond the schema and annotations, giving the agent essential information about scoping and persistence.

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 around 60 words and contains no fluff. Sentences are front-loaded with the core purpose, followed by usage triggers, then behavioral details, and finally sibling links. Every sentence earns its place without 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 storage tool, this description covers everything an agent needs: what it does, when to use it, how data is stored and scoped, persistence rules, and how to retrieve/delete it later. The absence of an output schema is acceptable because the operation is a save, and the description implies the effect without needing to enumerate return values.

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?

The input schema already has 100% coverage with descriptions for 'key' and 'value'. The description reinforces the relationship between the two by calling it a 'key-value pair' and adds the scoping behavior ('scoped by your identifier'), which adds meaning beyond the schema. The examples in the schema further clarify parameter usage.

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 function: 'Save data the agent will need to reuse later — across this conversation or across sessions.' It uses a specific verb ('Save'), names the resource (key-value data), and distinguishes itself from its siblings (recall, forget) by mentioning pairing and retrieval.

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?

It provides explicit when-to-use guidance: 'Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject).' It also differentiates between authenticated and anonymous sessions, clarifying persistence expectations. It explicitly references siblings with 'Pair with recall to retrieve later, forget to delete.'

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

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes, e.g., geology tools vs. Polymarket tools vs. memory tools. The main ambiguity is between ask_pipeworx and ask_pipeworx_grounded, but their descriptions clearly differentiate them (grounded vs. casual). Overall, an agent can reliably select the right tool.

Naming Consistency3/5

Names use snake_case consistently, but the structure varies: some are verb_noun (find_columns), some are noun_noun (entity_profile), some are single verbs (forget). This mix reduces predictability, though each name is still readable.

Tool Count3/5

With 29 tools, the server covers many domains (geology, finance, prediction markets, memory, subscriptions). This is a large surface for a server named 'Macrostrat', which implies a geology focus. The count feels bloated for a coherent set, though each tool individually seems justified.

Completeness4/5

The tool set is quite complete for its diverse sub-areas: geology has lookup tools, Pipeworx/Poly market has search, comparison, arbitrage, and memory/subscriptions have full CRUD. Minor gaps exist (e.g., no detailed geology unit edits), but overall coverage is strong.