Skip to main content
Glama

Flow Leaderboard / Outliers

get_flow_scan
Read-only

Cross-symbol options/stock flow leaderboard (biggest buyers/sellers by net notional) and flow outliers (most imbalanced symbols) across the universe. asset: 'options' | 'stocks'. kind: 'leaderboard' (ranked net notional buyers/sellers) | 'outliers' (flow outlier scan, ranked by absolute net notional).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesScan type: 'leaderboard' (biggest buyers/sellers) | 'outliers' (flow outlier scan)
assetYesAsset class: 'options' | 'stocks'
limitNoMax rows (leaderboard: per side 1–50 via 'n', default 10; outliers: 1–200 via 'limit', default 20). Passed as 'n' for leaderboard, 'limit' for outliers.
apiKeyNoFlashAlpha API key. Omit when calling via /mcp-oauth (OAuth flow); required on /mcp.
windowMinutesNoLook-back window in minutes (1–10080, default 240).

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the description doesn't need to restate safety. It adds context about the two scan kinds and the universe-wide scope, but doesn't disclose return format, pagination, or any other behavioral traits beyond what annotations provide. This is sufficient but not rich.

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 a compact two-sentence structure that packs essential information (asset, kind, per-kind behavior) without redundancy. Every phrase earns its place, and no filler words exist.

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

Completeness3/5

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

For a tool with 5 parameters and no output schema, the description explains the two required params and the limit/kind nuances, but leaves out details like return structure or pagination. It's adequate for selecting and invoking, but a bit light on what to expect from the response.

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?

Schema covers 100% of parameters, so baseline is 3. The description adds meaningful context by explaining the 'limit' parameter's dual behavior ('n' vs 'limit') and clarifying the semantics of 'kind' beyond the schema. This extra detail elevates it above baseline.

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 it provides a cross-symbol flow leaderboard and outliers scan, with specific verbs like 'leaderboard' and 'outliers'. It distinguishes itself from siblings by specifying the two kinds and asset scope, making its purpose unambiguous.

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 provides clear context on when to use it (for cross-symbol flow leaderboards or outlier scans) and explains the two modes (leaderboard vs outliers). It doesn't explicitly mention alternatives or exclusions, but the sibling list and the description's specificity imply appropriate use cases.

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

A3.6/5.0
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