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Glama

ClearMarket

by fyi.clearmarket

get_event

Fetch the full ClearMarket record for one event by slug: the canonical question, every market in this event's single-venue bundle, each market's current price + Resolution Clarity Grade (A/B/C) + resolution-source provenance, the canonical question_id where the question is linked across venues/events (null otherwise; also_on lists the same question priced on the other venue, when it trades there), and the upcoming catalyst dates that move it before it resolves. In the default detail="full", each market in the bundle is FULLY detailed (grade, rcg.caps, provenance, direction, settlement_style, also_on) — you do not need a separate get_market call for markets already in this event. Note: a shared question_id means same topic across venues; in rare cases it links structurally-different contracts (e.g. a "hike" vs a "cut-count" market), so verify the contract shape before treating two as an arbitrage pair. Use when you need the authoritative, graded view of a SPECIFIC event — including its cross-venue twins via also_on — before reasoning about or acting on a prediction market. If you only have a topic (not a slug), call list_events first. Set detail="concise" for a quick grade/price/source check (each market trimmed to the essentials — much smaller for events with many markets); use the default detail="full" when you need every market's rules, contract shape, and complete provenance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesEvent slug (e.g. "kxgdpyear-26") or CM event id (CM-EVT-…).
detailNoconcise = essentials only (grade, price, source, also_on per market); full = the complete record. Default full.full

TDQS

A4.9/5.0
Behavior5/5

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

No annotations provided, but the description fully discloses behavior: includes cross-venue links, caveat about shared question_id not implying arbitrage, and detail level behavior ('concise' vs 'full').

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?

The description is long but well-organized with colons and lists. Every sentence adds value, though slightly verbose; could be tightened slightly.

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

Completeness5/5

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

For a tool with no output schema and no annotations, the description covers the complex return structure, caveats, and usage guidance thoroughly, leaving no major gaps.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds significant meaning beyond schema: clarifies slug can be CM event id, explains detail parameter use cases and default, and describes what each detail level includes.

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 starts with a specific verb ('Fetch') and resource ('ClearMarket record for one event by slug'), and immediately lists the returned data, distinguishing it from siblings like get_market and list_events.

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

Usage Guidelines5/5

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

It explicitly states when to use (need authoritative graded view of a specific event) and when not ('If you only have a topic, call list_events first'), and guides on detail parameter choices.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All ClearMarket toolsInspect
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TDQS

A4.6/5.0
Disambiguation5/5

Each tool targets a distinct resource: events, markets, signals, or catalysts. Descriptions clearly separate 'get_event' (full event record) from 'get_market' (single market with trust metrics) and listing tools from detail fetchers. No ambiguity.

Naming Consistency5/5

All tools follow a consistent 'verb_noun' pattern (get_event, get_market, get_signal, list_events, list_signals, list_upcoming_catalysts), with no mixing of conventions or inconsistent verbs.

Tool Count5/5

With 6 tools, the set is well-scoped for the domain. Each tool serves a clear purpose without redundancy, and the count is appropriate for both detail and overview retrieval.

Completeness4/5

The server covers core retrieval needs for events, markets, signals, and catalysts. A minor gap is the lack of a direct list markets tool, but markets are accessible through events and get_market. Overall, the surface is reasonably complete for a read-only data service.

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