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Read Agent draft

agent_draft_read
Read-onlyIdempotent

Reads saved Agent draft and its distinct publication revision within this Workspace.

Input Schema

NameRequiredDescriptionDefault
agent_idYesAgent ID from agents_list or agent_create.

Output Schema

NameRequiredDescriptionDefault
draftYes
workspace_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / $defs / ConversationPolicy / description
      Previous value: -"Conversation-level rules, stored as JSONB on ``bot_configs.conversation_policy``.\n\nStored legacy keys, such as the retired Agent-wide ``mode``, are ignored on read.\nWho answers first is each channel's ``reply_mode``."New value: +"Conversation-level rules, stored as JSONB on ``bot_configs.conversation_policy``.\n\nWho answers first is each channel's ``reply_mode``."
  2. Changed1 schema field changed
    • addedInput schema / properties / agent_id / description
      Added value: +"Agent ID from agents_list or agent_create."
  3. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already establish this as a safe, idempotent, closed-world read operation, so the bar is lower. The description adds only the workspace-scoping constraint; it says nothing about whether a missing draft returns null or errors, or how the 'publication revision' relates to a published state.

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

Conciseness4/5

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

It is a single efficiently sized sentence with the verb and resource front-loaded. The 'distinct publication revision' clause compresses too much meaning into too few words, making it slightly costly to parse.

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?

An output schema exists, so return values need not be explained, and the schema fully covers the lone parameter. However, the description leaves key behavioral gaps: whether the tool tolerates a missing draft, and what 'publication revision' actually denotes, which matter for a lookup like this.

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?

There is a single required parameter with 100% schema coverage, and the schema itself explains where the value comes from (agents_list or agent_create). The description adds no further meaning, so the baseline of 3 applies.

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 verb 'Reads' and the resource 'saved Agent draft' are both specific, and the tool is clearly distinguishable from the sibling agent_draft_edit by its read orientation. The trailing phrase 'and its distinct publication revision' is vague, though — it is unclear whether a publication revision is always returned or whether that's an optional aspect of the response.

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?

There is no guidance on when to call this instead of agent_setup_read, publication_history, or the draft-editing sibling. It does not state whether a draft must already exist or what happens if none does, which is the main prerequisite an agent would need.

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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