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Read a conversation

read_conversation
Read-only

One conversation with its recent messages and the contact: name, whether they follow the account (Instagram only), tags, opt-out. AI drafts waiting for approval show as status draft.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
workspaceIdNoWhich workspace this is for. Only needed when the account has more than one — the error tells you the ids when it matters. Leave it out if it is already decided; do not ask the person again.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Added

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds useful behavioral details: it returns recent messages only, includes contact fields like tags/opt-out, notes Instagram-specific follow status, and explains that AI drafts appear as 'draft' status.

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 two tight sentences with no filler. The core purpose ('one conversation with its recent messages and the contact') is front-loaded, and the draft-status note is a valuable addition without bloating the text.

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

Completeness4/5

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

Given the tool is read-only and has no output schema, the description does a good job outlining return contents and special cases. It could be more explicit about what 'recent messages' includes or any pagination, but the provided detail is sufficient for an agent to call it correctly.

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 coverage is 50%: the workspaceId parameter is already well explained in the schema, and id is self-evident as the conversation identifier. The description does not add parameter-level meaning, but the schema handles the only ambiguous parameter, leaving no meaningful gap.

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

Purpose4/5

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

The description clearly states the tool reads a single conversation and returns its recent messages plus contact details. It is specific about the resource and scope, though it does not explicitly name sibling tools like list_conversations or get_contact to differentiate them.

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

Usage Guidelines2/5

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

No guidance is given on when to use this tool versus alternatives. It implies use when you need one conversation's recent messages and contact info, but it does not mention list_conversations for browsing multiple conversations or get_contact for contact-only details.

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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