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Set automatic drafting

set_auto_draft

Says whether an incoming message has Iris draft an answer on its own. With it off, a draft is written when someone asks for one from the inbox, which is what keeps the model spend where you put it.

Input Schema

NameRequiredDescriptionDefault
auto_draftYestrue has every incoming message drafted, false leaves the drafting to a person, from the inbox.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses what happens when the setting is off and suggests a cost-control implication, but it omits permissions, scope (user/workspace), immediacy of effect, and reversibility of the setting.

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?

The description is two sentences and appropriately sized for a simple boolean setting. The second sentence adds useful context about manual drafting and cost, though the first sentence could be more front-loaded and direct.

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?

For a simple one-parameter setting with full schema coverage and no output schema, the description covers the basic effect and off-state behavior. It remains incomplete regarding setting scope, permissions, and whether changes apply immediately, which matters for a mutation tool with no annotations.

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 one required boolean parameter and schema description coverage is 100%, so the schema already defines true/false behavior clearly. The description adds context about the off state and model spend but does not add syntax or operational detail beyond the schema.

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

Purpose3/5

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

The description conveys that the tool controls whether Iris automatically drafts replies to incoming messages, but the phrasing 'Says whether' is imprecise for a setter and could momentarily read as a getter. It does not explicitly name sibling tools or contrast with manual drafting tools such as save_compose_draft.

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

Usage Guidelines3/5

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

The description implies usage by explaining that turning it off means drafts are written only when requested from the inbox, and hints at model-spend control. However, it does not state when an agent should call this tool versus leaving settings alone or using related drafting tools.

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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