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Glama

Box

by io.github.pipeworx-io

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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

A4.3/5.0
Behavior4/5

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

The description adds valuable behavioral context beyond annotations: key-value pair scoping, persistent memory for authenticated users vs. 24-hour retention for anonymous sessions. This complements the annotations (readOnlyHint false, idempotentHint true) without contradiction, providing a fuller picture of the tool's behavior.

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?

Description is appropriately concise and front-loaded: the first sentence states the primary action, followed by usage guidance, storage characteristics, and companion tool references. Every sentence adds value with no fluff or 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 2-parameter write tool with no output schema, the description covers purpose, when to use, persistence semantics, scoping, and related tools. There is no significant missing context; the annotations handle non-destructiveness and idempotency, completing the picture.

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?

Input schema covers 100% of parameters with descriptions and examples. The description adds minimal parameter meaning beyond restating key-value storage, though it does suggest the kinds of value content (findings, addresses, preferences, notes). Since schema coverage is high, a 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?

Clearly states the tool's purpose with a specific verb ('Save data') and identifies what it saves (data for reuse later). Provides concrete examples (resolved ticker, target address, user preference, research subject) and distinguishes it from sibling tools by explicitly naming recall and forget as companions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context for when to use: 'Use when you discover something worth carrying forward... so you don't have to look it up again.' It also instructs to pair with recall for retrieval and forget for deletion, effectively guiding usage relative to related tools. However, it doesn't explicitly state when not to use it, leaving alternative storage mechanisms unaddressed.

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

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, aided by detailed descriptions (e.g., ask_pipeworx vs. ask_pipeworx_grounded). However, some overlap exists among Pipeworx-based tools (compare_entities, entity_profile, recent_changes, validate_claim) that could cause confusion without careful reading.

Naming Consistency3/5

Snake_case is used, but naming patterns are mixed: some start with verbs (ask_pipeworx, validate_claim), others with nouns or prefixes (box_get_file, entity_profile). This inconsistency makes it harder to predict tool names.

Tool Count3/5

At 31 tools, the server covers an unusually broad set of domains (cloud storage, data queries, betting, memory, subscriptions). This is on the heavy side and could benefit from splitting into more focused servers.

Completeness3/5

Gaps exist: Box storage lacks create/update/delete, Polymarket tools offer analysis but no execution, and some data domains (e.g., weather) have only indirect coverage. The surface feels uneven across the wide scope.

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