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Glama

Scream Void

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

A4.7/5.0
Behavior5/5

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

Description adds behavioral context beyond annotations: key-value scoping by identifier, persistence details (authenticated vs anonymous). 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, front-loaded with purpose, no wasted words. Every sentence adds value.

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?

Covers all necessary context: purpose, usage, persistence, pairing with siblings. Complete for a simple 2-parameter tool without 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 covers both parameters with descriptions (key, value). Description adds example patterns but does not significantly add meaning beyond schema. 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?

Description clearly states the tool saves data for later reuse, with specific verb ('save') and resource ('data'). It distinguishes from siblings 'recall' and 'forget', making purpose 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?

Explicitly tells when to use (discover something worth carrying forward) and mentions alternatives ('Pair with recall to retrieve later, forget to delete'). Provides clear context.

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

A3.8/5.0
Disambiguation2/5

Many tools overlap significantly in purpose, especially the ask_pipeworx variants (standard, beta, grounded) and deep_research, as well as the polymarket arbitrage/edges/fill_risk/kalshi_spread suite. It would be hard for an agent to reliably choose the correct tool without deep understanding of subtle distinctions.

Naming Consistency3/5

Tool names mostly use snake_case, but there is no consistent prefix or verb pattern. Some names are descriptive phrases (e.g., scream_void_scream, compare_entities) while others are vague (e.g., forget, recall). The mix of 'pipeworx_' prefix on some tools and lack of it on others adds inconsistency.

Tool Count3/5

32 tools is on the high side for a data research server, given the overlapping functionality. Some tools could be merged (e.g., the ask_pipeworx variants, polymarket tools). However, the count is not excessive enough to be unmanageable, and each tool serves a specific niche.

Completeness4/5

The server covers a broad range of data sources and prediction market analysis, with tools for research, comparison, monitoring, and memory. Minor gaps exist (e.g., no tool to update stored memories or manage subscriptions beyond CRUD), but core workflows are well-supported.

Resources