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 description does not disclose behavioral traits beyond the obvious (sending a report). Annotations indicate idempotentHint=true, which is not addressed. No contradiction, but the description provides minimal 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?
Two concise sentences front-load the purpose and provide a key instruction. Every word adds value with no 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?
With no output schema and 3 parameters with 0% schema coverage, the description inadequately explains return values or outcomes. It only covers one parameter partially, leaving the agent without complete context.
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 coverage is 0%, so the description must compensate. It clarifies the conversation parameter's purpose but does not explain the context or message parameters beyond the obvious. Partial compensation, leaving gaps.
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 is specific and distinct from the sibling tools, which are mostly related to open finance operations.
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 gives guidance on including the conversation array for reproduction, but does not explicitly state when to use this tool vs alternatives or any exclusions. The context signals show no similar sibling tools, so the usage is implied.
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.
Most openfinance_* tools target distinct resources and actions, but several overlap in purpose: list_transactions vs list_transactions_by_item, get_credit_card_bill vs list_credit_card_bills, and multiple connection/status tools expose reconnect URLs. The long descriptions help, but the boundaries are not always immediately obvious.
The openfinance_* tools follow a consistent list_/get_ verb_noun pattern and share a clear prefix. The smaller platform cluster is less consistent — marketplace, connect, authenticate, show_version, toolkit_info — mixing nouns, bare verbs, and snake_case, but it is a minor deviation overall.
At 25 tools, this sits at the heavy end of acceptable. The Open Finance surface is broad enough to justify many of them, but there is redundancy (e.g. list_transactions_by_item largely wraps list_transactions plus account resolution) and a separate platform-management cluster that makes the set feel sprawling.
The Open Finance domain is well covered: connection lifecycle, accounts, balances, transactions, credit-card bills, loans, investments, categories, and provider status are all present, and data flows connect properly between tools. Minor gaps exist, such as no single-transaction fetch or dedicated prompt-management tools, but the marketplace tool fills those roles.