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 readOnlyHint=false, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that the conversation array is needed for reproduction, which is useful but does not disclose what happens after reporting (e.g., how the feedback is processed). This adds some but not rich behavioral context.
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 two short sentences, front-loaded with the purpose and ending with a practical instruction. Every word earns its place; no wasted content.
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 3-parameter tool with no output schema, the description is decent but has notable gaps. It omits explanation of the context parameter and does not mention any return/confirmation behavior. Annotations help, but 0% schema coverage increases the description's burden.
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 explicitly explains the conversation parameter and implicitly covers message ('Report a bug...'). However, the context parameter is not mentioned, leaving a gap in parameter understanding.
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 function with a specific verb and resource: 'Report a bug, missing feature, or send feedback.' It is distinct from all sibling tools, which focus on financial data operations, so purpose clarity is high.
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 provides explicit usage guidance: 'Include the conversation array with recent messages for reproduction.' This tells the agent what to provide when invoking the tool. While no alternatives are mentioned, no sibling tool offers bug reporting, so the guidance is clear enough.
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 openfinance_* family is largely well-differentiated by resource and action, but the monolithic `marketplace` tool bundles search, invoke, install, billing, and prompt-library actions into one name, creating ambiguity about where platform capabilities live. Additionally, `openfinance_list_transactions` and `openfinance_list_transactions_by_item` both return transaction data and could be misselected despite their different aggregation intent.
The openfinance_* tools consistently follow a clear verb_noun pattern, which gives the majority of the surface a predictable shape. But the generic platform tools mix bare verbs (`authenticate`, `connect`), nouns (`marketplace`, `toolkit_info`), and verb_noun names (`report_bug`, `show_version`), so the server has two naming dialects rather than one uniform convention.
At 25 tools, this sits right at the top of the heavy range, and the server genuinely spans two broad domains: MCP platform administration and Open Finance banking data. The count is defensible given the breadth, but it is not a lean or easily navigable surface for an agent.
The Open Finance side is quite complete, covering connections, accounts, transactions, credit card bills, loans, investments, categories, provider status, sync, and disconnection. The platform side covers authentication, connection status, marketplace operations, bug reporting, and versioning, though some marketplace sub-actions are packed into one tool and bank connection itself is only reachable through URLs returned by other tools.