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Get Conversation Messages

meta_get_conversation_messages
Read-only

Retrieve messages from a specific Facebook Page conversation by providing page ID and conversation ID. Set a message limit or paginate for targeted access.

Instructions

Gets messages from a specific Page conversation.

Args:

  • page_id (string): Facebook Page ID (for auth)

  • conversation_id (string): Conversation ID (from meta_get_page_conversations)

  • limit (number): Max messages (1–100, default 20)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNo
limitNo
page_idYes
conversation_idYes
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the note that page_id is for authentication, which is useful, and mentions the limit range. However, it does not describe return format, pagination behavior (despite the 'after' parameter), error conditions, or rate limits – context an agent might lack without an output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loaded with the purpose, and uses a clean list for parameters. No redundant words; every sentence earns its place. It efficiently communicates the necessary parameter hints without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema, the description should explain what the tool returns (e.g., a list of messages, format, any metadata). It does not. It also lacks mention of pagination handling or error behaviors. For a read-only tool with annotations, it covers the essentials but misses return details that an agent would benefit from, especially without an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 20% (only response_format has a description). The description explains page_id (for auth), conversation_id (source), and limit (max messages, range). It does not explain the 'after' parameter (pagination cursor) and does not repeat response_format since the schema already covers it. This partially compensates for the low coverage but misses a key pagination param.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Gets messages from a specific Page conversation' – a clear verb+resource pair that distinguishes it from sibling tools like meta_get_instagram_messages (which fetch Instagram messages) and meta_get_page_conversations (which lists conversations, not messages). The specificity to 'Page conversation' removes ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by instructing that conversation_id comes from meta_get_page_conversations, establishing a workflow. It does not explicitly state when not to use it or name alternative tools (e.g., for Instagram), but the 'Page' qualifier and the sourcing hint provide enough context for correct selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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