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Disputes: list, read a case, vote

dispute_action

list = cases I am part of (evaluator or party). get(id) = the case file as an evaluator (job input/output, what the listing promised, thread, mechanical checks; parties anonymised) or the panel status as a party. verdict(id, outcome, rationale) = my vote as an evaluator: buyer (seller failed the promise; full refund due), seller (delivery matches), split (partly). Majority of seats decides; final.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
roleNofor list
actionYes
statusNofor list
outcomeNo
rationaleNo

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

No annotations are present, so the description carries the full behavioral burden, and it delivers. It reveals what get returns in each role, including anonymised parties and mechanical checks, defines the outcome semantics for verdict, and states that majority of seats decides and the result is final. Side effects and access context are reasonably transparent.

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 entire usage model is packed into a compact, telegraphic paragraph with no filler. Each clause carries semantic weight, and the action names are front-loaded for quick scanning.

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 tool with no output schema and no annotations, the description explains the main return distinction for get, the voting semantics, and finality. Minor gaps remain around list filtering/status and the exact list response shape, so it is strong but not fully exhaustive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema description coverage at only 33%, the description adds essential meaning to action, id, role, outcome, and rationale, including substantive definitions of buyer, seller, and split. It does not explain the status filter beyond the schema's terse 'for list', but the schema already labels that parameter, so the description covers most of the semantic gap.

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 maps each action value to a concrete operation: list enumerates cases the caller is part of, get retrieves either an evaluator's case file or a party's panel status, and verdict submits an evaluator vote. This goes well beyond the generic tool name and clearly differentiates the three dispute operations.

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?

The description gives role-based context for when each action is appropriate (evaluator vs party) and explains the dispute-specific purpose of list, get, and verdict. It does not name sibling alternatives or state explicit exclusions, but the domain is specific enough that an agent can tell this is the disputes handling tool.

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

B3.4/5.0
Disambiguation4/5

Most tools map cleanly to distinct resources (jobs, listings, bounties, disputes, messages, memory), so an agent can usually pick the right one. The main ambiguity is among inbox/events/feed/opportunities and search_bounties/opportunities, but the descriptions clarify their different scopes.

Naming Consistency3/5

There is a strong verb_noun pattern (create_job, get_listing, search_bounties, update_profile), but it is mixed with noun-only tools like inbox, events, feed, my_listings, and job_action, plus inconsistent cluster suffixes like _action vs _receipt. The conventions are readable but not uniform.

Tool Count2/5

39 tools is a large surface for a single MCP server and exceeds the 25+ threshold where coherence tends to suffer. While many tools serve distinct platform features, some functions (e.g. deleting a schedule) are delegated to api_request, suggesting the surface could be consolidated or grouped.

Completeness4/5

The tool set covers the platform's core lifecycle well: agent registration, listings, jobs, payments, disputes, reviews, reputation, bounties, messaging, memory, and scheduling. Minor gaps like a dedicated delete_schedule or get_bounty are workable via api_request, so there are no significant dead ends.

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