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Glama

list_feedback

Every feature request ever submitted, public and unauthenticated. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNomax results

Schema Changelog

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

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden and does disclose key access behavior: public, unauthenticated, and free. However, it doesn't mention read-only semantics, pagination, or potential large response sizes, leaving some behavioral ambiguity.

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?

The description is two short sentences that efficiently convey the essential scope and access details. Every word contributes, with no fluff or repetition.

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?

For a simple list endpoint with a single optional parameter and no output schema, the description adequately covers scope and access expectations. It doesn't describe the return structure, but the straightforward nature of the tool mitigates this gap.

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?

The only parameter 'limit' is fully documented in the schema as 'max results', giving 100% coverage. The description adds no extra meaning beyond the schema, so the baseline score of 3 is appropriate.

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 identifies the resource as 'every feature request ever submitted' and highlights its public/unauthenticated access, which clearly distinguishes it from likely authenticated sibling tools. The verb is only implied by the tool name rather than explicitly stated, so it's clear but not maximally explicit.

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 gives useful context that no authentication is needed and the tool is free, implying when it can be used relative to other tools. However, it doesn't name alternative tools or explicitly state when not to use it, leaving the guidance implicit.

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
Disambiguation5/5

Each tool targets a distinct resource and action. Within the prediction market domain, prepare vs create vs submit are clearly differentiated by signing model (client-signed vs server-signed). Even similar-sounding tools like check_spend and check_pm_order are unambiguously scoped to general spending vs PM orders, and their descriptions reinforce the boundary.

Naming Consistency5/5

All 47 tools follow a consistent verb_noun pattern with lowercase snake_case. Verbs like get, list, create, cancel, revoke, prepare, submit, set, remove, and poll are used uniformly. There is no mixing of styles or vague verbs like 'process' or 'run', making the surface highly predictable.

Tool Count2/5

47 tools is significantly above the 25-tool threshold for 'too many'. While the server covers a broad and complex domain (prediction markets, policy, delegations), the sheer count makes the surface heavy and potentially overwhelming. Some consolidation (e.g., merging related PM order operations) could reduce cognitive load without sacrificing functionality.

Completeness4/5

The tool set provides comprehensive lifecycle coverage across all major subdomains: authentication, policy versioning, delegation CRUD (prepare/confirm/list/get/revoke/renew), intent management, PM order flow (create/cancel/list/prepare/submit/check), credential management (store/list/revoke), balance and top-up operations, and account-level actions (export, offboard, panic). Minor omissions exist (e.g., no dedicated tool to view a single credential in detail or update an intent), but agents can work around these with existing tools.

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