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Get review queue

get_review_queue
Read-onlyIdempotent

Human exception-review queue (read-only). Returns items from data/review/queue.json for Ho Hum (sole human operator). Default status=open; pass status=all for history. Approve/reject is offline file edit only — write_api is always false; there is no unauthenticated write/approve API. Agents must never auto-clear trust flags or invent CE/EINs/donate URLs to close tickets.

Input Schema

NameRequiredDescriptionDefault
statusNoFilter by item status (default open on the server)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, but the description goes further: it discloses the backing file, the sole human operator, that write_api is always false, that approve/reject is offline file editing, and that agents must never auto-clear trust flags or invent CE/EINs/donate URLs. This is meaningful behavioral context beyond the annotation set.

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 purpose and default behavior are front-loaded, and the safety constraints come after, which is a sensible order. It is slightly dense with five clauses, but each sentence carries real operational or safety content, so it is appropriately sized for a read-only queue tool with write-adjacent risks.

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?

With one optional parameter, full schema coverage, and read-only annotations, the description supplies everything needed: what the queue is, whose queue it is, default and historical filtering, and the crucial fact that mutations are offline-only and must not be improvised. No output schema exists, but no return-value details are necessary for a straightforward filtered list.

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?

Schema coverage is 100% and the schema already documents the status enum and default, so the baseline is 3. The description adds value by explaining what the 'all' enum value means ('pass status=all for history'), which is more than the bare enum list conveys, though the default status=open is repeated from the schema.

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 names a specific verb ('Returns items') and resource ('Human exception-review queue'), plus the exact backing store (data/review/queue.json). It also distinguishes this read-only queue from offline approval workflows, so an agent can identify its role 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 Guidelines5/5

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

It states the default (status=open) and explicitly says to pass status=all for history, giving concrete selection guidance. It also clarifies when NOT to use it for writes ('Approve/reject is offline file edit only ... there is no unauthenticated write/approve API'), which is exactly the kind of when/when-not routing an agent needs.

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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