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Oxford Ledge

by com.oxfordledge
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Fundamentals Screen

ol_fundamentals_screen
Read-only

Threshold screen over up to 10 caller-supplied tickers (extras named in dropped) on latest-year SEC EDGAR XBRL fundamentals. Optional criteria: min_revenue, min_free_cash_flow, min_ebit_margin_pct, min_gross_margin_pct, max_debt_to_assets_pct, min_current_ratio, min_net_income (whole USD; *_pct as percentage numbers). Each result carries verdict: pass, fail (a reported value misses a threshold, in failed_criteria) or unknown (a metric not filed for the latest year, in unevaluated_criteria; unknown is not a fail). Not a universe screen; a fundamentals filter, NOT a buy signal. Source: SEC EDGAR company-facts XBRL.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "tickers": "<tickers>"
    },
    "name": "ol_fundamentals_screen"
  }
}

Input Schema

NameRequiredDescriptionDefault
tickersYes2-10 candidate ticker symbols to screen (hard-capped at 10).
min_revenueNoMin latest-year revenue (USD).
min_net_incomeNoMin latest-year net income (USD).
min_current_ratioNoMin current ratio.
min_free_cash_flowNoMin latest-year free cash flow (USD).
min_ebit_margin_pctNoMin EBIT margin (percent).
min_gross_margin_pctNoMin gross margin (percent).
max_debt_to_assets_pctNoMax debt-to-assets (percent).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only supply readOnlyHint=true; the description carries the real behavioral load. It discloses result semantics (verdict: pass/fail/unknown, failed_criteria vs unevaluated_criteria), that unknown is not a fail, the overflow behaviour (extras named in `dropped`), and the data source — genuinely useful context beyond the annotation.

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?

Dense but front-loaded: the core operation and the 10-ticker cap come first, then criteria, then result semantics and caveats. Every clause carries information, though the single long sentence is heavy and could be broken for scanability.

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 compensates by explaining the result shape (verdict, failed_criteria, unevaluated_criteria) and the dropped-tickers overflow. For a read-only screening tool with full schema coverage, nothing essential for correct invocation is missing.

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 each parameter's unit and meaning are already documented (USD, percent). The description's restatement of units ('whole USD; *_pct as percentage numbers') and the criteria list adds only marginal value beyond the schema, so baseline 3 applies.

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 states a specific verb+resource with scope: a threshold screen over up to 10 caller-supplied tickers on latest-year SEC EDGAR XBRL fundamentals. It also pre-empts misidentification with siblings/neighbours by declaring 'Not a universe screen; a fundamentals filter, NOT a buy signal', so an agent can tell it apart from get_fundamentals or ol_peer_fundamentals 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?

Usage context is clear: it is a multi-ticker (2-10, hard cap) fundamental threshold filter with optional criteria, and explicitly not a universe screen or buy signal. However, no alternative tool is named for the single-ticker or peer-comparison case, so the when-to-use-vs-sibling routing is left implicit.

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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