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get_debt_maturities

Read-only

Forward debt maturity ladder parsed from the latest 10-K/20-F footnote. Returns {ticker, maturities:[{year, amount}], thereafter, confidence, confidence_score, source, validation}. AMOUNTS ARE IN MILLIONS OF USD, not raw dollars -- 400 means $400M. THE LADDER IS AS OF the filing date, not today: the current-year bucket may already be repaid or refinanced. Check validation (the balance-sheet cross-check) before quoting a total. Every empty answer carries refusal_reason and a readable refusal_note. For historical issuance/repayment use get_capital_allocation. Source: SEC EDGAR 10-K note extraction. Requires Plus tier. Caveats ride the response's tool_notes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock ticker symbol (e.g. AAPL)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

With only readOnlyHint available, the description carries real behavioral burden and delivers: unit convention (millions USD, 400 = $400M), as-of-filing-date staleness caveat, balance-sheet cross-check, refusal fields on empty results, Plus-tier requirement, and tool_notes. This is exactly the context annotations cannot supply.

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?

Front-loaded with what the tool is and its most error-prone trap (units), then caveats, then the sibling route. Dense but every sentence carries a distinct operational fact; nothing is 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?

No output schema exists, so the description must describe returns — and it does, enumerating the returned fields including refusal_reason/refusal_note. Combined with units, provenance, tier gating, and validation guidance, an agent has everything needed to call and interpret it.

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 coverage is 100% for the single ticker parameter, so the schema already documents it fully. The description adds no syntax or format nuance beyond the schema, so the 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?

States a specific verb+resource (forward debt maturity ladder) plus its exact provenance (latest 10-K/20-F footnote) and the response shape. It also names a sibling (get_capital_allocation) as the route for a different need, letting an agent distinguish it without opening schemas.

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?

Gives clear conditions: forward maturities as of the filing date, with get_capital_allocation named for historical issuance/repayment, and an instruction to check `validation` before quoting a total. It does not address the closely related sibling ol_maturity_wall, leaving that routing to inference.

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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