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Scream Void Scream

scream_void_scream
Read-onlyIdempotent

Submit a scream (required text) with optional intensity (mild/moderate/full_primal/corporate) into the void; returns a number unaffected by your suffering.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
screamYesYour scream. Type anything. It will not help.
intensityNoScream intensity

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
numberNoRandom number returned by the void

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added
  2. Removed
  3. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already convey read-only, idempotent, non-destructive behavior. The description adds that it returns a number unaffected by suffering, but this is mostly flavor. No contradictions.

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?

Single sentence, front-loaded with the action, no wasted words. Highly concise.

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?

The tool is simple, annotations cover safety, and output schema exists. The description is complete enough for an agent to understand what the tool does.

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 has 100% description coverage, so description adds little beyond restating the parameters. The joke about 'It will not help' is not substantive semantic guidance.

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 uses a specific verb ('Submit') and resource ('scream into the void') and clearly distinguishes from all sibling tools, none of which involve screaming.

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

Usage Guidelines3/5

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

The description implies usage (when you want to express frustration) but provides no explicit guidance on when to use vs when not, nor mentions any alternatives.

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.