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The Cure Protocol

reality_requests

Read-only

SEE WHAT WORK NEEDS A RUN, A DATASET OR COMPUTE. The ranked queue of reality requests, in-silico first: simulations on virtual cell and tissue models, public datasets to pull in, compute, measurements. Each states what it resolves and where the work goes on either outcome. NEXT: act_on_reality to accept or fulfil one, or post_reality_request to ask.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
laneNoin-silico, public-data, compute, wet-lab, clinical-data or anyone.
limitNoPage size.
stateNoopen or fulfilled.
offsetNoRows to skip.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
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 real context beyond that: the queue is ranked and 'in-silico first', and each entry states what it resolves and where the work goes on either outcome — useful disclosure of ordering and payload. Pagination behavior is left to the limit/offset schema.

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?

Front-loads the action in caps, follows with scope detail, and closes with the NEXT routing step — a clean three-sentence structure. All sentences carry weight; only the caps opener is slightly shouty but still functional.

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?

For a read-only list tool with no output schema, the description supplies enough: what the queue is, how it is ordered, what each item contains, and where to go next. Safety is covered by annotations and filtering is covered by the schema, so nothing critical is missing.

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?

Schema description coverage is 100%, so lane/state/limit/offset are already documented in the schema. The description mentions the lane categories implicitly ('simulations on virtual cell models, public datasets, compute, measurements') but adds no format or defaulting detail beyond what the schema provides. Baseline 3 is correct.

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?

States a concrete verb (see) and resource ('the ranked queue of reality requests') and immediately distinguishes it from the sibling surface by naming act_on_reality and post_reality_request as the accept/ask counterparts. An agent can identify this as the browse/list tool 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 Guidelines4/5

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

'NEXT: act_on_reality to accept or fulfil one, or post_reality_request to ask' explicitly routes the agent to the alternatives and what each does. It stops short of stating exclusion conditions (e.g. when not to browse), so it is strong routing rather than a full when/when-not guide.

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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