Skip to main content
Glama

pg_kalshi_resolution_calendar

Compliance briefing: which Kalshi markets resolve in the next N hours? Bucketed by 6h, 24h, 48h, 1 week. Flags markets in CFTC-sensitive categories (Elections, Politics). Use for daily surveillance prep — markets near resolution have highest insider-trading risk window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoOptional category filter
hours_aheadNoLook-ahead window (default 48h, max 168h)
min_open_interestNoOnly markets with at least this OI

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behaviors: bucketing by time windows, flagging CFTC-sensitive categories, and the look-ahead window. This goes beyond typical descriptions, though it omits output format details and any limitations.

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?

The description is four short, impactful sentences. It front-loads the purpose, then provides bucketing, flagging, and usage context. Every sentence earns its place with no filler.

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?

Given 3 optional params, no output schema, and no annotations, the description provides strong context: what it does, how results are organized, special flags, and when to use it. It lacks explicit return-structure details, but is sufficient for a read-only calendar tool.

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?

The schema has 100% coverage for all three parameters, so baseline is 3. The description adds minor context by tying hours_ahead to the listed buckets and mentioning Elections/Politics as relevant categories, but it does not substantially extend the schema definitions.

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 clearly states the tool lists Kalshi markets resolving in the next N hours, with specific bucketing (6h, 24h, 48h, 1 week) and a special flag for CFTC-sensitive categories. This distinguishes it from sibling tools like pg_kalshi_market_details or pg_kalshi_search, which focus on different aspects.

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

Usage Guidelines4/5

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

The description explicitly recommends use for 'daily surveillance prep' and explains the risk window rationale. It does not explicitly mention alternatives or when not to use, but the context is clear and actionable.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation5/5

Each tool has a clear, distinct purpose covering different aspects of prediction market integrity (market analysis, wallet analysis, AML/KYC, alerting, reporting). There is minimal overlap risk, as even related tools (e.g., pg_insider_signal_scan vs. pg_information_advantage_score) are differentiated by input (market vs. wallet) and output type.

Naming Consistency4/5

All tools share the 'pg_' prefix and use descriptive snake_case names, making the set predictable. However, the verb/noun order is inconsistent (e.g., pg_whale_add vs. pg_market_details). The pattern is still clear and functional, so minor deviation from a strict verb_noun pattern.

Tool Count4/5

With 33 tools, the set is large but well-scoped for a comprehensive platform covering market analysis, wallet intelligence, compliance, and reporting. Each tool serves a distinct function, and the count is justified by the breadth of the domain, though it pushes the upper bound of 'reasonable'.

Completeness5/5

The toolset covers the full lifecycle of prediction market integrity work: from market discovery and integrity scanning to wallet analysis, entity resolution, AML/KYC, watchlist management, alerting, and SAR reporting. There are no obvious gaps for the stated purpose.

Resources