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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. Added

TDQS

A4.7/5.0
Behavior5/5

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

The description adds significant behavioral context beyond annotations: memory is scoped by identifier, authenticated users get persistent memory, anonymous sessions retain for 24 hours, and it notes relationships with recall/forget. No contradictions with annotations (readOnlyHint=false, idempotentHint=true, destructiveHint=false).

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 sentences, each earning its place: purpose in the first, usage examples in the second, storage/persistence details and sibling relationships in the third. Front-loaded with the core verb and resource.

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 write operation with full schema coverage, annotations, and clear usage guidance, the description is complete. It explains the full lifecycle (save, retrieve, delete) without needing an output schema.

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 documentation covers 100% of parameters (key, value) with clear descriptions and examples. The description's mention of key-value pair adds no new semantic detail beyond what the schema already provides, so baseline 3 is appropriate.

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' — a specific verb and resource (key-value memory). It distinguishes itself from sibling tools by explicitly pairing with recall and forget, making its role in the memory toolset unambiguous.

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?

Explicit guidance on when to use: 'Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject)'. It also directs to alternatives: 'Pair with recall to retrieve later, forget to delete', which prevents misuse.

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

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-duplicates, while deep_research, validate_claim, and bet_research blur the same routing/grounding line. The polymarket_* family also has five tools covering edges, arbitrage, fill risk, and edge decay with significant functional overlap, making misselection likely despite very detailed descriptions.

Naming Consistency2/5

Naming mixes verb_noun tools (get_pair, compare_entities, suggest_questions) with noun-style tools (entity_profile, recent_changes, bet_research) and bare verbs (remember, recall, forget). The polymarket_ and pipeworx_ prefixes add some structure, but overall the naming is inconsistent and doesn't follow a predictable pattern.

Tool Count1/5

The server is named 'exchangerate' but exposes 33 tools, only two of which (get_pair, get_rates) relate to exchange rates. Even as a general data platform 33 tools is at the extreme high end, and for the stated server purpose the count is wildly inappropriate.

Completeness1/5

For an exchange-rate server, the surface is severely incomplete: there is no historical rate lookup, no amount conversion, no supported-currency listing, and no rate-change monitoring. The actual tool content covers a broad research platform, but that is entirely mismatched with the server name, leaving the implied exchange-rate domain almost completely uncovered.