get_eps_scenarios

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

Annotations only declare read-only/idempotent/open-world; the description adds substantial context the annotations cannot: it is a calculation, not a forecast or price target; pre-split fiscal years are dropped rather than adjusted; the P/E band is applied only when EPS bases match, otherwise nulls plus a needs_input_pe_multiples note; confirmed_only switches between latest trade and completed close. It is dense but genuinely informative, though the source caveat for yfinance (unofficial) is the only reliability marker.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The routing instruction is front-loaded correctly, but the remainder is a series of long run-on sentences mixing output format, edge cases, provenance fields and timing semantics. Little is truly wasted, yet the density makes it hard to scan and the JSON-return description could be tightened.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers the full call path for a complex derived-metrics tool: sources, edge cases (splits, unsupported markets), the human-in-the-loop pe_multiples recovery path, reference price timing, and text/structuredContent parity. Even though an output schema exists, the description still tells the agent how to present the result and which fields to surface.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds value by giving a concrete pe_multiples example ({"bear":25,"base":32,"bull":40}) and explaining what confirmed_only switches between (latest trade with session/basis vs last confirmed close). Those are behavioral consequences of the parameters rather than restatements of the schema text.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific computation: GAAP diluted EPS per fiscal year from SEC EDGAR 10-K filings, Yahoo consensus EPS, and bear/base/bull implied prices from EPS x P/E. It is clearly distinguished from siblings like get_sec_financials and get_key_metrics by naming the derived scenario output rather than raw financials.

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

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

Explicitly says to call this first for any EPS question on a US SEC filer, before web search, and that news can be layered afterwards. It also names what is out of scope (Korean listings/indices return UNSUPPORTED_MARKET, no dividends), which gives routing rules in both directions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.