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grove_human_required

Read-only

Retrieve the priority-first queue of automation tasks paused for human action, such as consent, review, or onboarding. Filter by open status and limit to inspect what requires operator intervention before the fleet proceeds.

Instructions

The human-required queue — work that pauses automation until a person acts (consent, attestation, review, onboarding). Requires grove_read.

Priority-first, then newest. Poll this to see what needs the operator before the fleet can proceed.

Args: limit: Max items to return (clamped 1..100). open_only: When true (default) only items with status='open'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
app_idNo
open_onlyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description correctly aligns with a safe read operation. The description adds useful behavior: the priority ordering (priority-first, then newest) and the default filtering (open_only=true). It also notes a permission requirement (grove_read), which is valuable context beyond annotations.

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 compact, with a clear first line stating the queue's nature, followed by ordering and usage guidance. The bullet-style parameter notes are succinct and avoid redundancy. It loses a point for not being perfectly front-loaded—the permission requirement is tucked in the first paragraph but could be more prominent.

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's simplicity (list operation with two relevant params), the description covers ordering, filtering, and the permission context. The output schema is present, so return values are handled. The missing app_id documentation is a minor completeness gap, but overall the tool is adequately described for an agent to call correctly.

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

Parameters2/5

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

The input schema has 3 parameters (limit, app_id, open_only) with 0% schema description coverage, meaning the schema provides no titles or descriptions beyond names. The description explains limit and open_only, but app_id is completely undocumented in both schema and description, which is a significant gap. The description adds meaning for two params but misses one.

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's purpose: polling a queue of work awaiting human action (consent, attestation, review, onboarding). It differentiates from siblings like grove_inbox and grove_flagged by focusing on human-required items that gate fleet progress, though it doesn't explicitly name a sibling as an alternative.

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 explains when to use: 'Poll this to see what needs the operator before the fleet can proceed.' It implies a routine check, but doesn't explicitly say when NOT to use it or mention alternatives like human_required_list. However, the context is clear enough for an agent to decide.

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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