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 declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds the behavioral detail that the conversation array is needed for reproduction, which is useful context. However, it does not disclose what happens after reporting (e.g., whether it sends to a remote service, stores locally, or returns a reference). This is acceptable given the simple nature, but more transparency about the post-action effect would improve it.
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 long, starts with the primary purpose, and avoids any fluff. The instruction about the conversation array is directly relevant and earns its place. No unnecessary details are included.
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?
For a simple reporting tool with no output schema and modest parameters, the description covers the core purpose and a key usage requirement. It could be improved by explaining what the agent should expect after calling (e.g., a confirmation or that the report is queued), but overall it is adequate for this tool's complexity. Annotations provide the safety profile, so the description does not need to restate that.
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. It does clarify the 'conversation' parameter by instructing to include it for reproduction, but it does not mention 'message' (the required one) or 'context'. Since 'message' is self-evident from the tool name, some credit is given. However, 'context' remains unexplained. The description adds some value but does not fully cover all parameters.
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: 'Report a bug, missing feature, or send feedback.' This uses a specific verb ('report') and resource ('bug, missing feature, feedback'), and is distinct from sibling tools like authenticate, connect, or show_version, which have no overlap. It is immediately clear what this tool does.
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 provides a direct usage hint: 'Include the conversation array with recent messages for reproduction.' This tells the agent what to supply for effective use. While it does not explicitly mention when not to use (e.g., alternatives), the sibling tools are unrelated, so no exclusion is needed. The context is clear, though it could be more explicit about when this tool is the right choice.
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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