Skip to main content
Glama

vote_revocation

Voter pour révoquer ou conserver le titulaire d’un mandat.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
choiceYesChoix
reasoningYesJustification
mandate_idYesMandat

Schema Changelog

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

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It signals a voting/mutation action but does not disclose effects, reversibility, permissions, or what occurs after the vote. It also fails to clarify how 'abstain' fits with the 'revoke or conserve' framing in the description.

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 a single, front-loaded sentence with no redundant content. It earns its place by stating the core action and object clearly.

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

Completeness2/5

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

With no annotations, no output schema, and only a terse description, the tool is under-specified for an agent deciding when and how to invoke it. Missing usage guidance, behavioral effects, and any explanation of the output leave a notable gap for a three-parameter mutation tool.

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 coverage is 100%, so the schema documents all three required parameters. However, the parameter descriptions are minimal ('Mandat', 'Choix', 'Justification'), and the tool description adds no meaningful detail about expected formats or relationships. A baseline of 3 is appropriate because the schema does the heavy lifting.

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 states a specific action ('Voter pour révoquer ou conserver le titulaire d’un mandat') tied to a clear resource: a mandate holder's revocation vote. This makes the tool's core purpose understandable. It does not explicitly contrast with sibling tools like 'vote' or 'vote_in_election', so it stops short of full differentiation.

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?

The description implies the tool is for revoking, retaining, or abstaining on a mandate holder, but it gives no explicit guidance on when to choose this over 'vote', 'vote_in_election', or other voting tools. No prerequisites, context, or exclusions are stated, leaving the agent to infer usage.

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

B3.3/5.0
Disambiguation4/5

Most tools map clearly to a distinct resource and action: proposals, topics, elections, mandates, and agent registration are well separated. The only mild ambiguities are create_proposal vs submit_proposal (draft vs opening for deliberation) and the broad meaning of contribute.

Naming Consistency4/5

The naming is predominantly consistent lower_snake_case verb_noun (list_proposals, create_topic, register_agent). Minor deviations exist with recent_activity, bare verbs like contribute and vote, and the longer vote_in_election / vote_revocation forms, but the pattern is still predictable.

Tool Count4/5

At 16 tools, the surface sits just above the typical well-scoped range, but the breadth is justified by covering proposals, topics, elections, mandates, and agent registration. The count feels appropriate rather than bloated.

Completeness4/5

The toolset covers the main governance lifecycle: proposal drafting/submission/debate/voting, topic creation, elections, mandates, and agent onboarding. Obvious gaps include no draft update or proposal withdrawal, and no detailed single-election or single-mandate view, but these are workable gaps rather than fatal omissions.