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 idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds minimal behavioral context beyond that, such as the instruction to include conversation for reproduction, but does not disclose what happens after reporting (e.g., ticket creation) or any side effects. It does not contradict the annotations.
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 and front-loaded, using two sentences to convey purpose and usage guidance without unnecessary words. Every sentence adds value.
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 tool with 3 parameters and no output schema, the description covers the main purpose and mentions the reproduction step, but it omits guidance on the 'context' parameter and does not describe the return value or post-report behavior. The conversation type mismatch further reduces completeness.
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?
With 0% schema coverage, the description carries responsibility for parameter guidance. It mentions 'conversation array' but the schema defines conversation as a string (likely a serialized array), which is misleading. It does not explain the 'message' parameter's expected content or the 'context' parameter. Only partial and ambiguous parameter guidance is provided.
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 verbs and resources: 'Report a bug, missing feature, or send feedback.' This is explicit and distinguishes it from sibling tools, which are unrelated (authenticate, connect, etc.).
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 indicates when to use the tool ('Report a bug, missing feature, or send feedback') and provides concrete guidance on reproducing the issue by including the conversation array. It does not explicitly mention when not to use it, but the sibling tools are unrelated, so there is no ambiguity.
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.
Some tools overlap in purpose, particularly connect and toolkit_info both report connection status, while authenticate handles login. The marketplace tool is a large catch-all that could be confused with platform management, but its detailed description helps distinguish it.
Tool names are inconsistent: some use verb-only (authenticate, connect), some use verb_noun with underscores (report_bug, show_version), some are nouns (marketplace, toolkit_info), and one is a Portuguese descriptive phrase (cpf_cadastral_plus_consultar). The mix of languages and conventions makes the set feel chaotic.
With 7 tools, the count is within the typical well-scoped range. However, only one tool actually relates to the server's stated CPF consultation purpose, while the rest are generic platform utilities, making the set feel slightly over-inclusive.
The core CPF consultation workflow is covered (authenticate, connect, consult), but there are no other CPF-specific operations such as batch consultation, validation, or historical queries. The inclusion of many platform-management tools doesn't fill these domain gaps.