Skip to main content
Glama

FlashAlpha

by com.flashalpha.lab

Earnings Screener

get_earnings_screener
Read-only

Cross-sectional earnings screener: ranks upcoming events by VRP richness, cheapest implied move, highest historical IV crush, or importance. Returns implied-move percent, premium ratio (implied / realized-median), median historical IV crush, and richness assessment for each event. Configurable forward window, row limit, and minimum importance filter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoForward window in days (1–60, default 14).
sortNoRanking: 'vrp_richest' (default), 'cheapest_move', 'highest_crush', or 'importance'.
limitNoMax rows returned (1–300, default 20).
apiKeyNoFlashAlpha API key. Omit when calling via /mcp-oauth (OAuth flow); required on /mcp.
min_importanceNoOnly include events with importance >= this value.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, so safety is established. The description adds meaningful behavioral context by detailing what it returns (implied-move percent, premium ratio, median IV crush, richness assessment) and the ranking logic, going beyond the annotations without contradiction.

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?

Three concise sentences front-loaded with purpose, followed by output details and configuration options. No filler or redundant phrasing—every sentence earns its place.

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 compensates by listing the key return metrics and configuration knobs. It stops short of defining 'richness assessment' or typical edge cases, but for a read-only screener with this complexity, it is largely complete.

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 covers all 5 parameters with full (100%) descriptions, so the parameter semantics baseline is 3. The description's mention of 'forward window, row limit, and minimum importance filter' adds no unique detail beyond the schema's own parameter descriptions.

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?

Description opens with 'Cross-sectional earnings screener' and specifies ranking dimensions (VRP richness, cheapest move, highest crush, importance), plus output fields. This clearly distinguishes it from sibling get_earnings_calendar or get_earnings, which are event-specific.

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 term 'cross-sectional' implies comparing many upcoming events, which is useful context, and the description notes configurable parameters. However, it does not explicitly name alternative tools or state when not to use this tool.

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

All FlashAlpha toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation2/5

Many tools have overlapping scopes: get_stock_summary, get_volatility, get_vrp, and get_exposure_summary all return comprehensive analytics with shared metrics, making it hard to pick the right one. The flow family (get_flow_live, get_flow_summary, get_flow_scan, get_flow_signals, etc.) has significant redundancy — get_flow_live bundles data also available via separate tools.

Naming Consistency4/5

Tool names mostly follow a consistent get_<noun> pattern, with clear subgroups like get_historical_* and get_*_exposure. Minor deviations exist: post_screener, post_structure_pnl, calculate_greeks, and solve_iv break the get_ convention, but they are still predictable and readable.

Tool Count1/5

With 73 tools, this is far beyond the 3–15 tool sweet spot and even the 50+ extreme mismatch threshold. While the domain is broad, the enormous surface is bloated by near-duplicate historical replay variants (18 get_historical_* tools) and multiple overlapping summary endpoints, making it unwieldy for an agent.

Completeness5/5

The tool set provides thorough coverage of options analytics: quotes, chains, greeks, volatility surface, VRP, exposure, flow, historical replay, screening, and strategy analysis. There are no obvious dead ends — core workflows like calculating greeks, getting exposure, and screening the universe are all supported.

Resources