report_bug
Report a bug, missing feature, or send feedback. Include the conversation array with recent messages for reproduction.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| context | No | ||
| message | Yes | ||
| conversation | No | [] |
Report a bug, missing feature, or send feedback. Include the conversation array with recent messages for reproduction.
| Name | Required | Description | Default |
|---|---|---|---|
| context | No | ||
| message | Yes | ||
| conversation | No | [] |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false and destructiveHint=false. The description adds the context of including the conversation array, but does not disclose side effects such as ticket creation or rate limits, so it provides some value but not rich detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the tool's purpose, and contains no unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 parameters and no output schema, the description is adequate but not complete. It covers the tool's purpose and gives a key hint about the conversation parameter, but lacks detail on message and context parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate fully. It adds meaning to the 'conversation' parameter by calling for recent messages, but the required 'message' and 'context' parameters remain unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reports bugs, missing features, or feedback, with a specific verb and resource. It naturally distinguishes itself from sibling tools like connect or marketplace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly say when to use this tool vs alternatives, but the purpose is clear. It instructs including the conversation array for reproduction, which is a usage hint, though no exclusions or alternative mentions are made.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The platform tools (authenticate, connect, marketplace, toolkit_info) have overlapping responsibilities around auth, connection status, and available tools, making it unclear which to use for a given task. The single TSE tool is distinct, but the surrounding tool boundaries are fuzzy.
Names are inconsistent: single-word verbs (connect, authenticate), nouns (marketplace, toolkit_info), and one snake_case domain tool (titulo_votacao_consultar) with no shared pattern. A consistent verb_noun or verb_object format is missing.
Seven tools is a reasonable number, but the scope is muddled: six are generic MCP platform utilities, while only one addresses the server's stated TSE purpose. Most tools are unrelated to voting-title queries, so they do not earn their place in a TSE-focused server.
The TSE domain is served by a single query tool with no supporting operations (e.g., no history, no batch lookups, no formatting helpers), and the platform tools create a confusing meta-layer. The actual consultation surface is minimal, and the set feels incomplete for a dedicated TSE service.