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Open questions

open_questions
Read-onlyIdempotent

The referee's questions still waiting on their answer: one on-chain attention question per crypto event, "$SYM reads 40 or more at <event open + 24h> UTC", answered at_or_above (40 or more) or below (Under 40). Each carries the score and volume multiple at open, the three nulls frozen at creation (base rate: the share of past crypto events that read 40 or more 24 hours after open; persistence: the latest reading carried forward; always below) and Tickerz's own answer, which is the base-rate null. accepting_answers is true until 4 hours after the question opened; the crowd split stays null until then. calibration: hit rates of the crowd majority and each null over every resolved question, each with its n. Optional symbol filter. Same data as GET /api/questions?state=open. About attention, not price. Not advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoOptional ticker, e.g. HBAR

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds substantial behavioral context beyond that: accepting_answers is true until 4 hours after open, the crowd split stays null until then, and the three nulls are frozen at creation. It omits pagination/volume limits, so not a 5.

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 purpose is front-loaded in the first clause, but the body is a single dense run-on paragraph packed with domain-specific terms. Every sentence carries information, yet the wall-of-text structure hurts readability without a clear field-by-field breakdown.

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?

With no output schema, the description must carry the return-value burden, and it does explain the returned fields (score, volume multiple, three nulls, Tickerz answer, calibration hit rates). It is highly complete for a complex domain tool, missing only edge cases like empty/open-empty states.

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 coverage is 100% for the single symbol parameter, so the schema already documents it as an optional ticker. The description's 'Optional symbol filter' adds no syntax or format detail beyond what the schema provides, making the baseline 3 appropriate.

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 opening clause states a specific resource and state: the referee's questions still awaiting answers, explicitly mapped to GET /api/questions?state=open. It is distinguishable from the single-question sibling get_question, though heavy domain jargon ('referee', 'Tickerz') slightly obscures the plain purpose.

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?

It notes an optional symbol filter and that it is 'not advice', but gives no explicit when-to-use or when-not guidance and never routes the agent to alternatives like get_question, base_rate or board for related data. Usage must be inferred from the 'still waiting on their answer' phrasing.

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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