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annotate_wait

Hold the turn until the human approves and sends annotations, then return the batch to the agent. Use after opening the review panel and each batch to process new sends.

Instructions

Park until the human presses Send in the review panel, then return that batch. This is the main hand-off and the ONLY way a send reaches you on its own — an MCP server cannot start a turn, so with nobody parked a send just sits in the store until someone asks for it. Call this immediately after annotate_open and again after handling each batch. It is cheap to park: some clients (Claude Code) move a call still running after two minutes to a background task, so you keep working and the batch arrives as a task notification. The overlay shows the human a live indicator of whether anyone is parked.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
timeoutSecondsNoHow long to park before giving up. Default 3600 (1h), max 28800 (8h). Parking is free — no tokens are spent while blocked — so prefer the default over short waits. Long parks are kept alive with progress pings; the ceiling is the per-server `timeout` in .mcp.json.
Behavior5/5

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

With no annotations, the description fully discloses behavior: parking is free and token-free, clients may background the call after two minutes, long parks are kept alive with pings, there is a per-server timeout ceiling, and the overlay shows a live indicator. This goes far beyond minimal disclosure.

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 a compact paragraph where every sentence earns its place: purpose, rationale, usage timing, client behavior, and UI feedback. It is front-loaded with the core purpose and contains no filler or redundancy.

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

Completeness5/5

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

Given the tool's interactive waiting nature, the description covers what happens when no one is parked, what the caller experiences (background task), how long waits are kept alive, and what the human sees. It provides the necessary operational context despite no output schema or 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?

The schema already provides 100% coverage for the single timeoutSeconds parameter with rich detail on defaults, max, and behavior. The description itself adds no new parametric meaning beyond restating that parking is cheap. Baseline 3 is appropriate since the schema carries the full burden.

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 opens with a specific verb and resource: 'Park until the human presses Send in the review panel, then return that batch.' It clearly states the tool's core function and distinguishes it from siblings by calling it 'the main hand-off' and 'the ONLY way a send reaches you on its own.'

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

Usage Guidelines5/5

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

Explicit when-to-use guidance is provided: 'Call this immediately after annotate_open and again after handling each batch.' It also explains why this tool is necessary (MCP server cannot start a turn) and why alternatives won't work, giving clear contextual exclusions.

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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