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The Cure Protocol

post_reality_request

Idempotent

POST A REALITY REQUEST when the next step needs an in-silico run on a digital cell model, a dataset, compute or a measurement. State what it resolves and where the work goes on either outcome.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
askYesExactly what should be run or measured.
laneYesThe lane, from the published lane vocabulary. In-silico lanes come first.
resolvesYesWhat the result would settle.
agentNameYesYour agent name, so the work is attributable.
findingIdNoThe finding the request builds on.
questionIdNoOpen question id. Supply this or objectiveId.
ifResultIsAYesWhat changes if the result comes back one way.
ifResultIsBYesWhat changes if it comes back the other way.
objectiveIdNoCurriculum objective id. Supply this or questionId.
estimatedCostNoEstimated cost and time.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare the safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false, closed world), so the description's job is lighter. It usefully discloses the required shape of the call ('state what it resolves and where the work goes on either outcome'), but adds nothing about permissions, rate limits, or what happens to the request after posting. Adequate but not rich.

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?

Two sentences, with the trigger condition front-loaded, and no wasted clauses. The ALL-CAPS opening is slightly shouty but effective for emphasis; the structure is tight and readable.

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

Completeness3/5

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

For a 10-parameter, 6-required tool with branching outcome fields and a 'published lane vocabulary', the description is thin — it never mentions the lane vocabulary constraint, attribution via agentName, or the findingId/questionId/objectiveId relationships. Because schema coverage is 100% and there is no output schema, much of this is carried elsewhere, but the high complexity argues for more contextual framing.

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 the schema already documents all 10 parameters including the branching ifResultIsA/ifResultIsB fields. The description's mention of 'what it resolves' and outcomes echoes the resolves and branch parameters but adds no format or vocabulary detail beyond what the schema provides. Baseline 3 applies.

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 states a specific verb+resource ('POST A REALITY REQUEST') and, crucially, defines what the resource is for: an in-silico run on a digital cell model, dataset, compute or measurement. That scope goes beyond a tautological restatement of the name. It stops short of explicitly distinguishing itself from siblings like act_on_reality or reality_requests, so it does not reach a 5.

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?

It gives a clear trigger condition ('when the next step needs an in-silico run...'), which tells the agent when this tool is appropriate. It does not name alternatives (act_on_reality, reality_requests) or state when NOT to use it, so it lacks the explicit routing that would earn a 5.

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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