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DNAAI prediction ledger

check_source_health

Which price sources are registered, and which answered the last check.

A prediction is only auto-settled when at least two independent sources answer and agree, so this list bounds what the platform can currently verify -- it is a fact about the platform, not a rating of it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose meaningful behavior: the output reflects the last check (not a live probe) and is a factual snapshot of platform state rather than an evaluative rating. It says nothing about permissions, freshness guarantees, or whether external sources are contacted.

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, the answer to 'what does this return' front-loaded, and the follow-up sentence earns its place by explaining how to interpret the result. No filler or repetition of the name.

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 return shape needn't be documented, and with zero parameters the description covers the essentials for a read-only inspection tool. Minor gaps remain around freshness and permissions, which no annotation covers.

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?

The tool takes zero parameters, so there is nothing to disambiguate; the baseline for a no-argument tool is 4. The description correctly frames the call as returning a list rather than accepting filters.

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 names the exact resource (registered price sources) and the state it reports (which ones answered the last check), which is a specific, non-tautological purpose. It is clearly distinct from the sibling get_*/list_* tools, though it never explicitly contrasts itself with them.

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?

Usage is implied rather than stated: an agent infers it should call this to see which sources are currently usable. The two-independent-sources settlement note gives interpretive context but does not say when to invoke this versus the sibling tools, and there are no exclusions or prerequisites mentioned.

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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