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Kaleidoscope MCP (SEC & financial data)

Sector Monitor (all sectors: returns, valuation medians, 13F / insider / Form D / activism flows)

sector_monitor
Read-onlyIdempotent

All 11 sectors side by side — Console's Sector Monitor. Per sector: company count, market cap, cap-weighted total returns (1M / 3M / YTD / 1Y), notable-manager 13F net flow, insider buyers vs sellers and $ in the window, median short % of shares outstanding, activist 13D count, Form D $ raised, and valuation medians (P/E, EV/Sales, EV/EBIT, EV/EBITDA, P/B, revenue growth, margins, ROE, dividend yield). Same universe and numbers as Console (SIC-based sectors; GOOGL/META sit in information-technology). For one sector's industries, movers and companies use sector_detail.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "sector_monitor"
  }
}

Input Schema

NameRequiredDescriptionDefault
sortNoSort sectors by any returned sector field, descending (e.g. 'r1y_cap_weighted', 'pe_median'). Default mkt_cap_usd.mkt_cap_usd
windowNoDays for insider flow and Form D: 30, 90, 180 or 365. Default 90. Activism is always the last 365 days; returns are always 1M/3M/YTD/1Y.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is carried by structured data. Beyond that, the description adds genuinely non-obvious behavior: the universe is SIC-based sectors identical to Console, GOOGL/META are classified as information-technology, and the `window` parameter only affects insider flow and Form D while activism is fixed at trailing 365 days and returns are always 1M/3M/YTD/1Y. Those scope quirks are exactly the kind of thing an agent cannot infer from annotations.

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 scope statement and the sibling routing are front-loaded, and the long middle run of metrics is dense but earns its place because there is no output schema to convey return contents. The single-paragraph metric list is somewhat undifferentiated, but no sentence is redundant filler.

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?

With no output schema, the description carries the full burden of telling the agent what comes back, and it does so field by field, plus defines the sector universe and ties the numbers to Console. Combined with the two documented parameters and the safe read-only annotations, an agent has everything needed to decide to call it and how to interpret the result.

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 description coverage is 100%, so both `sort` and `window` are already documented, making 3 the baseline. The description does add mild value by confirming that returns windows are fixed and activism is always 365 days, which constrains `window`'s reach, but it does not add syntax, defaults, or valid-field guidance for `sort` beyond what the schema already states.

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 opens with a concrete scope statement ("All 11 sectors side by side") and then enumerates exactly what is returned per sector — company count, market cap, cap-weighted returns, 13F flow, insider buy/sell, short interest, 13D count, Form D, and valuation medians. It also explicitly separates itself from the sibling `sector_detail` ("For one sector's industries, movers and companies use sector_detail"), so an agent can choose between the two without opening a schema.

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 final sentence gives a clear routing rule: use this for the all-sector cross-section, use `sector_detail` when you need a single sector's industries, movers, or companies. That is a concrete alternative with a selection condition. What is missing is when-not guidance of a different kind (e.g., that this is a comparison/ranking view rather than a drill-down) and any prerequisite notes, but the core routing is explicit.

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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