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 establish that the tool is not read-only, not destructive, and idempotent. The description adds useful behavioral context by instructing the caller to include recent messages for reproduction, but it does not describe side effects (e.g., ticket creation), expected response, or whether the report is submitted anonymously. This is adequate given the annotation coverage but not rich.
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?
Two sentences with no filler. The first sentence states the core purpose, the second delivers the key usage instruction. Every word earns its place, and the critical guidance (include conversation for reproduction) is front-loaded and concise.
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 description is sufficient for a simple call: the user's complaint goes in 'message', and 'conversation' aids reproduction. However, it overstates the conversation requirement (it is optional with a default), omits the 'context' parameter entirely, and does not mention what happens after submission. Given no output schema and three parameters, more detail would help an agent invoke it correctly every time.
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 mentions the 'conversation array' and its purpose, but the schema defines 'conversation' as a string, not an array, which could mislead. It does not explain the required 'message' parameter or the optional 'context' parameter. The description only partially clarifies parameter semantics.
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 states a specific action ('Report') with clear targets ('a bug, missing feature, or send feedback'), making the tool's purpose immediately obvious. It is distinct from all sibling tools, which are authentication, marketplace, or Plaud-related operations, so there is no ambiguity with alternatives.
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 clearly indicates when to use the tool: whenever the user wants to report a bug, request a missing feature, or provide feedback. It also gives a practical hint to include the conversation array for reproduction. No exclusions or alternatives are needed because sibling tools serve entirely different purposes.
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 Plaud-specific tools are clearly distinct, but 'marketplace' is a mega-tool that appears to cover search, invoke, install, subscribe, prompts, and bug reporting — overlapping with connect, toolkit_info, and the standalone report_bug tool. An agent could easily pick the wrong entry point for connection status, installed tools, or feedback.
There is a clean plaud_get_* / plaud_list_* cluster, but the platform tools mix verbs and nouns: authenticate, connect, marketplace, report_bug, show_version, toolkit_info. The naming is readable and the Plaud prefix helps, but the overall pattern is inconsistent.
Eleven tools is a reasonable count and mostly well-scoped for a Plaud integration plus MCP platform management. It is slightly heavy because 'marketplace' bundles many sub-capabilities into one tool while several small utility tools exist separately.
The Plaud retrieval surface covers user, recordings, recording details, transcript, and AI notes, which is sufficient for the main use case of accessing Plaud data. Minor gaps exist around delete/update operations, but recordings are created externally by the hardware, so read-focused coverage is acceptable.