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get_capital_allocation

Read-only

Where a company sent its cash, up to 30 annual labels. Returns {ticker, capitalAllocation:{years, periods, dividends, netBuybacks, grossRepurchases, netDebtChange, acquisitions, sharesOut, isDilutive, basis, summary}} as PARALLEL ARRAYS aligned to years (newest first, fiscal labels). netBuybacks is a NET, DERIVED DILUTION PROXY, not a buyback figure (repurchases minus issuance, IPO proceeds and SBC); grossRepurchases is the filed line. Share-count cells on a pre-split basis are withheld, never shown as a phantom buyback. An IFRS reporter is REFUSED, never served zeros. Complements get_fundamentals and get_debt_maturities. Source: SEC EDGAR XBRL cash-flow tags, 24h cache. 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

A4.2/5.0
Behavior5/5

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

Annotations only carry readOnlyHint=true, but the description discloses substantial behavior beyond that: the parallel-array return shape, that netBuybacks is a derived dilution proxy rather than a filed figure, that pre-split share-count cells are withheld rather than shown as phantom buybacks, that IFRS reporters are refused rather than zero-filled, plus 24h cache and Plus tier. This is genuinely informative for correct interpretation.

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?

Front-loads the purpose before the dense return-field enumeration, and every clause carries signal (refusal, derivation caveat, cache, tier). It is long and reads as a wall of text, but the density is justified by the absence of an output schema.

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 takes on the burden of describing the return shape, the derivation semantics of key fields, refusal behavior, cache freshness, tier requirement, and where caveats live (tool_notes). Nothing essential for calling or interpreting the tool 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?

Only one parameter (ticker) with 100% schema description coverage, so the schema already does the work. Baseline 3 applies since the description adds no syntax or constraint beyond what the schema 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?

States a specific resource and scope: 'Where a company sent its cash, up to 30 annual labels.' It explicitly distinguishes itself from siblings with 'Complements get_fundamentals and get_debt_maturities,' so an agent can place it in the retrieval set without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Names adjacent tools (get_fundamentals, get_debt_maturities) and a tier prerequisite, which implies where it fits, but gives no explicit when-to-use/when-not guidance or condition for choosing this over those alternatives.

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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