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 provide safety flags (readOnlyHint=false, destructiveHint=false, idempotentHint=true). The description adds no extra behavioral context beyond that, so it neither contradicts nor significantly enhances transparency.
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 short sentences with no unnecessary fluff. It directly communicates the purpose and a key usage hint.
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, the description covers the essential action and a key input (conversation). It does not explain return values or post-report behavior, but given the lack of an output schema and the tool's simplicity, it is reasonably complete.
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 coverage is 0%, so the description must compensate. It explains the 'conversation' parameter by suggesting it holds recent messages for reproduction, but does not clarify 'context' or 'message'. Parameter names are self-explanatory, but the description adds only partial value.
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. It is distinct from sibling tools like authenticate or connect, so it stands out.
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 implies when to use the tool (when reporting issues) but does not explicitly state usage context or contrast with alternatives. It gives a hint about including conversation for reproduction, but lacks explicit guidance on when to prefer this tool over others.
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 distinct roles: authentication, connection status, marketplace, feedback, version, toolkit state, and the domain query. However, authenticate, connect, and toolkit_info all touch on connection/auth concepts, which could cause initial confusion.
The platform tools use varied patterns (single-word verbs, nouns, verb_noun combinations), while the domain tool uses a long descriptive snake_case name. This mix is readable but not uniform.
Seven tools is within a reasonable range, but six are generic platform utilities and only one serves the apparent domain purpose. The count feels inflated relative to the domain scope.
The domain surface is extremely thin with a single query operation. There are no other process-related endpoints (e.g., search, details, movements), making it a minimal but possibly complete read-only lookup.