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submit_prediction_job

Submit a prediction analysis job to analyze market trends. Optionally specify timeframe and provide payment proof for verifiable outcomes.

Instructions

Submit Prediction Analysis job @requirement: REQ-MCP-002 - Prediction market analysis @requirement: REQ-PAY-001 - Payment verification Properties: Alignment(+0.4), Self-Improvement(+0.3)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketYes
timeframeNo24h
payment_proofNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are present, so the description carries the full burden. It mentions 'Payment verification' requirement and properties like Alignment(+0.4), but these are opaque. There is no disclosure of side effects, auth needs, rate limits, or what happens after job submission.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief (two lines plus tags), but it lacks meaningful structure. The front-loaded phrase 'Submit Prediction Analysis job' is clear, but the requirements and properties are not well-integrated for an AI agent's consumption.

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?

Given the tool has 3 parameters, no annotations, and sibling tools that submit similar jobs, the description is incomplete. It does not cover what the job entails, what the inputs represent, or how the output is used (despite an output schema existing).

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not explain any of the three parameters (market, timeframe, payment_proof). It adds no semantic value beyond the parameter names and default values in the schema.

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 'Submit Prediction Analysis job', providing a clear verb+resource. It distinguishes from sibling tools like submit_oracle_job by specifying 'Prediction Analysis', though it could be more explicit about what constitutes a prediction analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description lacks context for appropriate usage scenarios, and the requirement references (@requirement: REQ-MCP-002, REQ-PAY-001) are not explained in terms of decision criteria.

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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