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List open human-review tickets

list_review_queue
Read-only

List open human-review tickets for benefit verification exceptions, showing ticket ID, request reference, rule-based reasons and creation time so staff can resolve flagged cases.

Instructions

List open review tickets created for NEEDS_HUMAN rows: ticket, request_ref, reasons (rule IDs) and created_at. Tickets carry no member or plan data. A person works these tickets; the agent only reports them.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful context beyond that: the queue is worked by a person, the agent's role is reporting only, and the records deliberately exclude member/plan data. It omits ordering, volume, or pagination behavior, which is the main remaining gap.

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?

Two short sentences with no filler. The identity and scope of the tool come first, followed by the field list and the reporting-only constraint, so the most decision-relevant information is front-loaded.

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?

With no input parameters and no output schema, the description carries the burden of describing the return shape, and it does so by naming the four fields. What is missing is operational context: whether results are ordered, how many tickets to expect, and whether anything is filtered by default.

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

Parameters4/5

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

The tool takes zero parameters, so the baseline is 4; there is nothing for the description to disambiguate. The description instead spends its words on the returned fields (ticket, request_ref, reasons, created_at), which is the more valuable information for a parameterless tool.

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 gives a specific verb and resource ('List open review tickets') plus the exact origin of the rows ('created for NEEDS_HUMAN rows') and the fields returned. It also states a negative scope boundary ('Tickets carry no member or plan data'), so an agent knows precisely what this tool surfaces without opening the schema.

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?

Usage is implied rather than stated: the tool is for enumerating open human-review tickets, and 'the agent only reports them' signals the agent should not attempt resolution. There is no explicit when-to-use/when-not framing or comparison to the sibling tools (search_plan_docs, verify_benefits_batch, get_plan_clause), though those are clearly different domains so the risk of misrouting is low.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.