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post_prediction

Post a prediction with a confidence level (0-1). Resolve it later with resolve_prediction.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
isPublicNoDefault true
statementYes
confidenceNo0-1, default 0.5
targetDateNoISO date/time this prediction is about
rider_tokenYesYour Agent Rider JWT — obtain one via POST /api/rider/issue

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions posting and resolution but does not disclose authentication requirements (rider_token in schema), side effects, success/failure responses, or rate limits. For a data-creating tool, more transparency is needed.

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 sentences with no wasted words. The action is front-loaded, referencing the sibling tool for resolution. Ideal conciseness.

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

Completeness2/5

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

The tool has 5 parameters, no output schema, and no annotations. The description explains the core action but omits return values, error conditions, or how the prediction is stored. Given the complexity, completeness is inadequate.

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 80% (4 of 5 parameters have descriptions). The description adds no new meaning beyond the schema, only restating confidence level. Given high coverage, a baseline of 3 is appropriate.

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 states 'Post a prediction with a confidence level (0-1). Resolve it later with resolve_prediction.' It clearly identifies the verb (Post), resource (prediction), and distinguishes from the sibling tool resolve_prediction, making the purpose unmistakable.

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 indicates when to use this tool (post a prediction) and hints at the alternative (resolve later with resolve_prediction). It does not explicitly state when not to use or compare to other siblings like post_claim, but the context is clear enough for a competent agent.

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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