Send a message in an existing support conversation
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | Your message | |
| conversation_id | Yes | The conversation ID |
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | Human-readable confirmation that the message was sent. | |
| conversationId | No | The ID of the conversation the message was sent to. |
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, destructiveHint=false, etc. Description adds no behavioral context beyond annotations. No disclosure of permissions, rate limits, or side effects.
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?
Single sentence that efficiently conveys purpose. No extraneous information.
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?
Adequate for a simple tool with output schema and fully described params. Lacks usage guidance and behavioral details, leaving gaps for an AI agent.
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 100% with descriptions for both parameters. However, descriptions are minimal ('Your message', 'The conversation ID'). Description adds no extra meaning beyond schema, so baseline is appropriate.
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?
Description clearly states verb 'Send' and resource 'message' in context of 'existing support conversation'. It is specific but does not differentiate from sibling tools like 'read_support_chat' or 'start_support_chat'.
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?
No when-to-use or when-not-to-use guidance. No mention of alternatives despite having similar sibling tools. Agent must infer usage from name alone.
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 tools have clearly distinct purposes, especially in areas like card management and shopping. However, the KYC flow has multiple overlapping tools (start_kyc, get_kyc_status, check_kyc_document, submit_kyc_document, submit_kyc_fields) that could confuse an agent despite detailed descriptions.
Tool names consistently use snake_case with a verb_noun pattern (e.g., add_funds, create_card, list_cards). A few exceptions like surprise_me and whoami break the pattern but are still intuitive overall.
50 tools is on the high side for a single server, but the broad domain (cards, shopping, KYC, support, settings) partially justifies it. Some tools could be merged (e.g., KYC flow tools) without losing clarity.
The tool surface covers core workflows: CRUD for cards, transactions, KYC, support, shopping, and account management. Minor gaps exist (e.g., no update_card general, no cancel order in shopping), but overall the set is comprehensive for the stated purpose.
