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Peer Fundamentals

ol_peer_fundamentals
Read-only

Side-by-side latest-fiscal-year fundamentals for a peer set (the FIRST 6 unique tickers; the rest are named in dropped). Returns {summary, count, peers, dropped, as_of}; a peer is {ticker, available, fiscal_year, revenue, net_income, eps_diluted, free_cash_flow, gross_margin_pct, ebit_margin_pct, debt_to_assets_pct, current_ratio, stockholders_equity}. Dollar figures are whole USD; *_pct are percentage numbers. ONE YEAR ONLY -- no history (use get_fundamentals). Fiscal years are each filer's own, so peers are NOT calendar-aligned. A ticker without XBRL coverage returns {ticker, available: false} (no metric keys), never dropped. No price leg, so no P/E or EV multiples. Source: SEC EDGAR company-facts XBRL; one cold EDGAR fetch per ticker.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickersYes2-6 ticker symbols to compare (hard-capped at 6).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

With only readOnlyHint available, the description carries the burden well: it discloses truncation behavior (first 6 unique tickers, rest named in `dropped`), the missing-coverage case ({ticker, available:false}, never dropped), the absence of a price leg (no P/E or EV), the data source, and the cost profile (one cold EDGAR fetch per ticker). These are exactly the behavioral traits annotations cannot convey.

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 compare scope leads, then the return shape, then constraints and caveats. Every sentence carries information, though the field list and unit notes make it longer than strictly necessary.

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?

No output schema exists, so the description must explain return values -- and it does, enumerating the response envelope and per-peer field names plus units (whole USD vs *_pct) and edge cases. Nothing an agent needs to call and interpret this correctly is missing.

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 coverage is 100% and the single parameter is documented, so baseline is 3. The description adds meaning beyond the schema by explaining what happens past the hard cap (first 6 kept, remainder reported in `dropped`), which the schema's 'hard-capped at 6' note only hints at.

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?

States a specific verb (side-by-side compare) and resource (latest-fiscal-year fundamentals) for a peer set, and explicitly names the sibling get_fundamentals as the alternative for history. An agent can distinguish this from ol_fundamentals_screen and get_fundamentals without opening any 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?

Explicitly says 'ONE YEAR ONLY -- no history (use get_fundamentals)', which gives a clear when-not plus the alternative. It doesn't address when to prefer this over ol_fundamentals_screen, so it stops short of full routing guidance.

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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