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Remember

remember
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

A4.9/5.0
Behavior5/5

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

Description adds context beyond annotations: key-value scoping by identifier, session vs persistent memory, 24-hour retention for anonymous. Does not contradict idempotentHint or other 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?

Four well-structured sentences, front-loaded with purpose, no wasted words. Efficiently covers purpose, usage, and behavior.

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?

Given no output schema (write tool), description fully covers storage behavior, persistence, and pairing with recall/forget. Complete for all relevant aspects.

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 coverage is 100% with clear descriptions. The description adds practical examples of key values (e.g., 'subject_property'), providing extra semantic guidance beyond the 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?

The description clearly states the tool saves data for reuse across conversations/sessions with specific examples (ticker, address, preference, research subject). It distinguishes from siblings 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 says when to use: when discovering something worth carrying forward. Provides context on persistence (authenticated vs anonymous) and mentions paired tools recall and 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

A3.6/5.0
Disambiguation2/5

The set mixes near-synonymous routers (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), overlapping discovery tools (discover_tools, suggest_questions), and several prediction-market scanners (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker) whose boundaries are easy to blur. The six onedrive_* tools are distinct, but they are buried in an unrelated toolkit where multiple tools appear to address the same task.

Naming Consistency2/5

Naming is split across several conventions: onedrive_*, polymarket_*, and pipeworx_* form consistent clusters, but top-level tools use bare verbs (remember, recall, forget), noun phrases (entity_profile, compare_entities), and varied styles (deep_research, generate_llms_txt, validate_claim). The pattern is readable within clusters, but not predictable across the server.

Tool Count2/5

37 tools is heavy, and the vast majority have nothing to do with the server's name 'Onedrive' — only 6 of 37 target OneDrive, while 31 span Pipeworx data, Polymarket betting, memory, and web utilities. This is a sprawling multi-domain bundle rather than a focused server.

Completeness1/5

As a OneDrive server, the surface is severely incomplete: it offers read-only coverage (list, search, get, profile, shared) but no upload, create, update, move, copy, delete, or share operations, and binary Office/PDF content returns unreadable bytes. The Pipeworx tools are individually comprehensive, but they do not fill the basic lifecycle gaps for the server's apparent file-management domain.