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Remember

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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

A4.4/5.0
Behavior4/5

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

Description adds details about scope, persistence across sessions, and 24-hour retention for anonymous users, complementing annotations that indicate idempotency and non-destructiveness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single paragraph front-loads purpose, then usage, then behavioral details; slightly verbose but every sentence is useful.

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?

All necessary context provided for a simple store tool: purpose, usage, parameter hints, persistence behavior, and pairing with related tools. No output schema needed.

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% and parameters are self-explanatory; description provides examples but no additional semantics beyond schema.

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?

Description clearly states 'Save data the agent will need to reuse later' with specific verb and resource, and distinguishes from sibling tools recall and forget.

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?

Explicitly describes when to use (discover worth carrying forward) and alternatives (pair with recall/forget).

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, especially within the Polymarket and data query groups. However, the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and the overlap between deep_research and ask_pipeworx for broader questions could cause minor confusion.

Naming Consistency3/5

Tool names follow some consistent prefixes (ask_pipeworx, polymarket_, scan_, recent_) but overall mix verb_noun, noun phrases, and standalone verbs (forget, recall, remember). This inconsistency reduces predictability, though the patterns are still readable.

Tool Count3/5

32 tools is high but justifiable given the server's dual role as a Pipeworx data gateway and Polymarket analysis suite. Each tool serves a distinct function in the workflow, but the count borders on heavy and could be streamlined.

Completeness4/5

The tool set covers the full lifecycle for the server's domain: discovery, querying, grounded answers, entity resolution, company profiles, fact-checking, prediction market analysis, memory, and monitoring. Minor gaps exist (no account management or direct data modification), but these are out of scope for a read-only data interface.