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 indicate readOnlyHint=false (expects side effects), destructiveHint=false, and idempotentHint=true. The description adds a behavioral guideline to include the conversation array for reproduction, which is useful. However, it does not disclose potential side effects (e.g., sending a report to a server) or other behavioral nuances beyond what annotations already imply.
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 consists of two concise sentences, front-loading the primary purpose before an actionable instruction. Every word earns its place, and there is no redundancy or vagueness. It efficiently conveys purpose and a key usage detail without unnecessary fluff.
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 tool with 3 parameters, no output schema, and annotations, the description provides adequate but not complete context. It explains the conversation parameter's purpose but does not clarify the 'context' field or expected behavior/return values. Still, for a bug-reporting tool, the description is sufficient for basic use, though missing details like response handling.
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?
The description directly explains the 'conversation' parameter by instructing to include recent messages for reproduction, adding value beyond the schema's defaults. However, it leaves 'context' and 'message' unaddressed, though 'message' is self-explanatory. With 0% schema coverage, the description only partially compensates for 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 uses a specific verb 'report' plus resources 'bug, missing feature, or send feedback', clearly stating the tool's purpose. It distinguishes itself from sibling tools like 'authenticate' and 'marketplace' by focusing on user feedback. The additional instruction about the conversation array further clarifies the tool's role.
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: when there is a bug, missing feature, or feedback to send. While it does not explicitly name alternatives or exclusions, no sibling tool serves a similar function, making the usage context clear. It could be enhanced by stating when not to use it, but the intent is straightforward.
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.
Only ecac_caixa_postal_consultar is clearly a domain tool; the others are platform/admin helpers whose boundaries overlap, especially connect, toolkit_info, show_version, and marketplace. marketplace itself also bundles list/report/install behaviors, so an agent must read carefully to avoid selecting the wrong status or support entry point.
Most platform tools use short English verbs or verb_noun names, but the single domain tool is Portuguese and follows an object-before-verb pattern: ecac_caixa_postal_consultar. marketplace and toolkit_info add non-verb noun-style names, so the overall set lacks a consistent and predictable naming convention.
Seven tools is not a high count by itself, but only one tool actually provides the ECAC/Caixa Postal service while the others are generic mcp.ai platform helpers. The set is semantically crowded with meta-tools rather than well-scoped to the named server purpose.
For a read-only official-source consultation service, ecac_caixa_postal_consultar plus the auth/connect/payment/marketplace workflows covers the core flow reasonably well. Minor gaps remain, such as a dedicated usage or credit-balance tool, but they are workable through the surrounding platform controls.