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 annotations include 'idempotentHint': true and 'readOnlyHint': false, suggesting the tool may have effects but is safe to retry. The description adds that the conversation array is needed for reproduction, but does not clarify whether retries cause duplicate reports, which is a behavioral gap.
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 (two sentences) and front-loads the primary purpose. It includes a practical instruction about the conversation array, but could be slightly more structured if it separated the purpose from usage details.
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?
Given the tool has 3 parameters, no output schema, and no schema coverage, the description only partially explains what to provide. It mentions the conversation array but omits any details about what the message and context parameters are for, or what happens after reporting, leaving it incomplete for effective use.
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 only mentions 'conversation' as the array to include, but does not explain the purpose of 'message' or 'context' beyond what the schema names imply. It fails to compensate for the lack of schema documentation.
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: reporting bugs, missing features, or feedback. It uses specific verbs and resources, but does not explicitly distinguish from sibling tools, although none of the siblings seem to handle bug reporting.
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 this tool (for reporting issues or feedback) but provides no explicit guidance on when not to use it or alternatives. The inclusion of 'Include the conversation array...' gives some context, but not a clear usage policy.
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 three openai_billing_* tools are clearly distinct, and the platform utilities (authenticate, connect, toolkit_info, show_version) mostly have separate roles. However, the marketplace tool is a sprawling mega-tool that overlaps with connect (auth URLs), toolkit_info (installation state), and even report_bug, making the boundaries fuzzy and increasing the chance of misselection.
Naming is mixed: some tools use a consistent openai_billing_ prefix with verb_noun structure, while others are bare verbs like authenticate and connect, or a bare noun like marketplace. There is no uniform pattern across the set, which makes it harder to predict tool names.
Nine tools is a reasonable count, but the marketplace tool packs in many sub-operations (search, describe, invoke, install, subscribe, prompts), so the effective surface is much larger than the count suggests. Still, the visible count is not excessive and each platform utility earns its place.
For the stated OpenAI Billing domain, the set covers account listing, cost reports, and usage reports, giving solid read-only coverage. Missing operations like invoice/payment details or account disconnection are minor gaps, and the platform tools add broader lifecycle coverage for connections and the marketplace.