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?
The description adds useful context beyond the annotations by specifying the need to include the conversation array for reproduction. However, it does not explain the operation's side effects beyond 'report,' nor does it clarify the implication of idempotentHint: true. Annotations already indicate a non-read-only, non-destructive operation, and the description aligns with that but omits further behavioral 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 concise, consisting of two sentences that are immediately relevant. It front-loads the core purpose and then provides one critical usage tip. Every sentence earns its place without unnecessary elaboration.
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?
The tool is simple with three parameters and no output schema, so the description need not be extensive. It covers the overall purpose and highlights the conversation parameter, but it lacks clarification for the required message parameter and any indication of what the user should expect as a result. This is adequate for basic understanding but leaves gaps for correct invocation.
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%, so the description must compensate by explaining parameters. It only mentions the 'conversation' parameter explicitly, leaving the required 'message' parameter and the optional 'context' parameter unexplained. This is a significant gap since 'message' is required for the call to succeed.
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's purpose with specific actions: 'Report a bug, missing feature, or send feedback.' This distinguishes it from all sibling tools, which are unrelated to reporting. It uses a clear verb and resource, making the tool's function immediately obvious.
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 gives explicit guidance on when to use the tool ('Report a bug, missing feature, or send feedback') and provides a crucial instruction: 'Include the conversation array with recent messages for reproduction.' It does not mention alternatives or exclusions, but the sibling tools do not overlap with this functionality, so the context is sufficient.
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.
Most tools have clearly distinct purposes, but connect and toolkit_info both report connection status, causing slight overlap. The domain-specific protestos_sp_consultar is unique and well-separated from the platform utilities.
Naming is inconsistent: one-word verbs (authenticate, connect), a noun (marketplace), an English verb_noun (report_bug, show_version), a noun_noun (toolkit_info), and a Portuguese compound (protestos_sp_consultar). No unifying pattern is evident.
Seven tools is within a reasonable range, but the server name suggests a specialized domain while only one tool is domain-specific. The other six are generic platform utilities, making the composition feel unbalanced for the stated theme.
The domain tool provides the core query capability, and the marketplace tool enables discovery and invocation of additional MCPs, covering many potential gaps. However, the domain-specific surface itself is minimal with no supplementary operations like reporting or export.