Skip to main content
Glama

The Committee

The Committee Convene

the_committee_convene
Read-onlyIdempotent

Convenes five random number generators. Each argues for their number. Democracy determines the result. One member always dissents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urgencyNoMeeting urgency
questionNoThe question before the committee. Optional.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoThe number agreed upon by the committee
dissentNoThe member who dissented
membersNoCommittee members and their arguments

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare the tool as read-only, non-destructive, and idempotent, covering the safety profile. The description adds a distinct behavioral quirk (one member always dissents) and a process detail (democracy), which goes beyond the structured hints and gives the agent a sense of the tool's inner workings.

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 short sentences, no wasted words. The first sentence identifies the core action, and the following two add relevant behavioral color. It is front-loaded and appropriately sized for the tool's simplicity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity, strong annotations, and existing output schema, the description is adequate. It captures the playful yet functional nature of the committee. The only gap is the lack of explicit usage guidance, but that's already reflected in the usage dimension.

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 description coverage is 100%, with both optional parameters (urgency, question) clearly described. The description adds no additional parameter context beyond what the schema provides, so it meets the baseline but doesn't enhance understanding of how parameters influence behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies a resource (five random number generators) and action (convenes), and the democratic process sets it apart from typical sibling tools. However, it doesn't explicitly state what the tool returns (e.g., a number or decision), so it's slightly less than fully clear.

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

Usage Guidelines2/5

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

No guidance is given on when to use this tool versus alternatives. It doesn't mention use cases like random decision-making or entertainment, nor does it reference any sibling tools or exclusion criteria. The optional 'question' parameter implies a purpose, but the description doesn't articulate it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation3/5

The ask_pipeworx family creates real ambiguity: ask_pipeworx_beta explicitly states it currently matches ask_pipeworx exactly, leaving an agent no principled way to choose between them. discover_tools and suggest_questions also overlap as meta-tools for navigating the catalog, though the remaining tools (five polymarket_* tools, entity tools, subscription lifecycle) are well-delineated by their detailed cross-referenced descriptions.

Naming Consistency3/5

The set is uniformly snake_case with coherent subfamilies (ask_pipeworx*, polymarket_*, pipeworx_*, remember/recall/forget), but it mixes imperative verb_phrase names (validate_claim, resolve_entity, generate_llms_txt) with noun_phrase names (entity_profile, recent_changes, ai_visibility_check), and the_committee_convene breaks the pattern entirely with a full-sentence name. The inconsistency is stylistic rather than chaotic, so it stays readable.

Tool Count2/5

At 32 tools, the set exceeds the 25+ threshold for 'too many' and the breadth is not fully earned: ask_pipeworx_beta is self-admittedly redundant right now, and several tools feel bolted on from unrelated domains (the_committee_convene, generate_llms_txt, scan_dependency, ai_visibility_check). The core data-research and prediction-market scope would be tighter and more navigable at roughly 20-24 tools.

Completeness4/5

The primary domain — authoritative data lookup, entity research, and prediction-market analysis — is covered with no dead ends: query (ask_pipeworx, grounded, deep_research), profile (resolve_entity, entity_profile, compare_entities), track (recent_changes), verify (validate_claim), bet research (bet_research, polymarket_edges, arbitrage, fill_risk, kalshi_spread), subscriptions (subscribe/unsubscribe/list/recent_alerts), and memory (remember/recall/forget) form complete lifecycles. Minor gaps exist only at the periphery: no execution layer for prediction-market trades (research stops at fill-risk advice) and single-tool coverage for the npm/llms.txt/AI-visibility side-domains.