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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

A4.7/5.0
Behavior4/5

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

Annotations already provide idempotentHint=true, but description adds valuable context about scope by identifier, persistent vs. anonymous session retention, and storage as key-value pairs. 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?

Three well-structured sentences: first states purpose, second provides usage guidance, third adds behavioral details. No fluff.

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?

Complete for a simple memory tool: no output schema needed, description covers all aspects (what, when, how stored, retention), and sibling tools are referenced.

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%, but description enhances with concrete key naming examples and explains the purpose of key-value pair storage 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 reuse across conversations/sessions, provides concrete examples (resolved ticker, target address, etc.), and distinguishes itself 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 tells when to use ('when you discover something worth carrying forward') and mentions alternatives (recall, forget) for retrieval and deletion.

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

A3.5/5.0
Disambiguation2/5

Several tools have blurry boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, polymarket_edges/polymarket_arbitrage/polymarket_edge_tracker/polymarket_fill_risk all target overlapping prediction-market signals, and ai_visibility_check vs scan_competitor_ai_presence plus entity_profile vs recent_changes vs compare_entities partially duplicate each other. The Webflow tools are distinct, but the dominant Pipeworx cluster is hard to navigate.

Naming Consistency2/5

Naming mixes multiple conventions: clean verb_noun for Webflow tools (list_sites, get_collection_item), an ask_pipeworx family, plain single verbs (remember, recall, forget), and long noun-cluster names for prediction markets (polymarket_arbitrage, polymarket_edge_tracker). There is no single predictable pattern across the set.

Tool Count1/5

36 tools is excessive for a server named 'Webflow' — only about six tools actually concern the Webflow CMS (list_sites, get_site, list_collections, list_collection_items, get_collection_item, generate_llms_txt). The remaining ~30 tools form a completely different data-research/prediction-market/memory suite, making the server wildly over-scoped and mislabeled.

Completeness2/5

For the Webflow domain, the surface is read-only: sites and collections can be listed and items fetched, but there are no create, update, delete, or publish operations, leaving obvious lifecycle gaps. The extensive non-Webflow tools do not address the stated server purpose, so the mismatch hurts completeness rather than fixing it.