DNAAI prediction ledger

list_events

List the questions this platform has published, each with its frozen spec.

An event's spec -- asset, operator, baseline day, target day, tolerance --
is fixed before anyone participates, which is exactly why its wording and
its settling rule cannot drift apart. Set `joinable_only` to true to see
only the events still accepting a number.

Returns the platform's own JSON, including `event_id`, `question`,
`resolve_by`, `join_closes_at`, `participants` and `join_open`.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`joinable_only`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 3, 2026

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the immutability property of event specs and the returned fields, but says nothing about auth requirements, pagination, or ordering behavior for what is a list endpoint.

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-loaded with the action and resource, and the filter instruction is easy to find. The middle sentence about frozen specs is domain flavor that is somewhat editorial but still reinforces the resource semantics, so it is not wasteful enough to penalize heavily.

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?

An output schema exists, so the description need not list return fields (its field enumeration is mildly redundant but harmless). For a single-optional-parameter list endpoint with no annotations, the description is complete enough for correct invocation.

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 0% and the single parameter joinable_only is only titled 'Joinable Only' in the schema. The description compensates by defining it precisely as showing 'only the events still accepting a number', which is real added meaning over the schema title.

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?

States a specific verb ('List') and resource ('questions this platform has published') and clarifies each carries a frozen spec. It is clearly the plural counterpart to the sibling get_event, though it does not explicitly name that sibling as an alternative.

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

Usage Guidelines3/5

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

The description explains the joinable_only filter's purpose ('only the events still accepting a number'), which implies one usage context, but it gives no explicit when-to-use guidance relative to get_event or the other siblings.

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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