get-converse-historyFetch converse conversation history via POST /v1/converse/get-conversation for one fbId.
| Name | Required | Description | Default |
|---|---|---|---|
| fbId | Yes | End-user fbId |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes | JSON or plain text body returned by the Botsify HTTP API |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey read-only, idempotent, and non-destructive behavior, lowering the burden. The description adds the endpoint and a single-fbId scope, which is useful but does not enrich behavioral understanding further (e.g., pagination, limits, or error semantics). No contradiction with 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 a single, well-structured sentence that is front-loaded with the action and resource. It avoids unnecessary words and includes the essential endpoint detail, making it highly concise without losing clarity.
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 one-parameter read tool with rich annotations and an output schema, the description covers the core purpose and scope. It could briefly mention when to use it relative to siblings, but the combination of schema, annotations, and the endpoint makes it sufficiently complete for an agent to invoke correctly.
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 fbId described as 'End-user fbId'. The description only repeats 'for one fbId', adding no new semantic depth beyond the schema. The baseline of 3 applies because the schema carries the parameter meaning adequately.
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 a specific verb ('Fetch') and resource ('converse conversation history') and includes the HTTP endpoint for precision. It implicitly distinguishes from sibling tools by focusing on 'converse' history for one fbId, which is a unique scope.
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 a usage context: it fetches history for a single fbId via a specific endpoint. However, it does not explicitly mention when to use this tool versus alternatives like list-conversations or get-user-chat, nor does it provide any exclusionary guidance. The context is clear but not fully fleshed out.
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.
Several tools have overlapping purposes, such as send-converse-message, send-inbox-message, send-user-message, and stream-user-message, which all deliver messages but with subtle differences. Similarly, list-bot-messenger-users and list-messenger-users both fetch messenger users, and start-builder-chat, clear-builder-conversation, and store-builder-response all manage builder chat state. Descriptions help, but the boundaries are still confusing.
Tool names consistently use hyphenated lowercase verb-noun format, but the verbs and nouns vary significantly in specificity. For example, 'get-query-response' vs 'query-mcp-agent' vs 'stream-user-message' all imply querying but with different styles. The pattern is readable but not highly predictable, with some names like 'change-user-activation' and 'patch-instruction-section' deviating from the simple verb_object structure.
With 44 tools, this server feels overloaded. The breadth covers bots, messaging, templates, whitelabel, and versions, but many tools could be consolidated (e.g., multiple message-sending variants). The count exceeds the 25-tool threshold for 'too many', making it difficult for agents to select the right tool without extensive context.
The tool set covers the main lifecycle: agent creation, versioning, deployment, deletion, messaging, conversation history, user management, template management, and whitelabel operations. Minor gaps exist, such as missing delete for WhatsApp templates or update operations for user attributes, but these are workable edge cases. Core workflows are well supported.