Fintel Discovery — Financial Intelligence for AI Agents

Get Earnings History & Estimates

GetEarningsHistory

Read-onlyIdempotent

    Fetch earnings history (EPS actual vs estimate, surprise %) and upcoming
    earnings dates with consensus estimates. Also returns forward EPS estimates
    by quarter and fiscal year.

    Use this tool when:
    - You want to see how a company has performed vs EPS expectations
    - You need the next earnings date and the consensus estimate
    - You are analyzing earnings surprise trends or growth trajectory

    Returns three sections: earnings_history, earnings_dates, earnings_estimate.

    Source: Yahoo Finance via yfinance. No API key required.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`params`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the read-only nature is covered. The description adds useful behavioral context beyond annotations: the Yahoo Finance/yfinance source, that no API key is required, and that the response is split into three named sections. No contradiction exists.

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?

The description is compact and front-loaded: one clear functional sentence, a bulleted 'Use this tool when' list, a one-line output summary, and a source note. Every sentence earns its place and there is no filler.

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

Completeness3/5

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

The description is strong for tool selection and explains the source, output sections, and no-key requirement. However, it gives no guidance on how to populate the params object, and with a top-level schema coverage of 0% and many unrelated fields in the nested schema, an agent lacks enough invocation support.

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

Parameters1/5

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

The description mentions no parameter names, formats, or required inputs. Context reports 0% schema description coverage, so the description must compensate for the nested params schema, and it does not; the agent is left to infer that symbol and limit are the relevant fields among many unrelated ones like wholesaler_ids and exclude_fillers.

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 opens with a specific verb and resource: 'Fetch earnings history (EPS actual vs estimate, surprise %) and upcoming earnings dates with consensus estimates,' and adds forward EPS estimates. This clearly distinguishes it from sibling tools like GetFinancials or GetAnalystRatings, which do not target earnings estimates and dates.

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?

The description provides an explicit 'Use this tool when' list covering performance vs EPS expectations, next earnings date/consensus, and surprise trend analysis. It does not name alternatives or state when not to use the tool, so it stops short of a 5.

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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TDQS

A3.9/5.0

Disambiguation4/5

Most tools target a distinct resource and action, with clear separation between search and detail tools (e.g., SearchIAPDFirm vs GetIAPDFirmDetail, SearchBrokerCheck vs GetBrokerCheckDetail). A few pairs like SearchBrokerCheck and SearchBrokerCheckFirm could cause momentary confusion, but descriptions clarify individual vs firm scope.

Naming Consistency4/5

The dominant pattern is consistent: Search* for discovery, Get* for retrieval, with CamelCase throughout. Minor deviations like LookupTicker and MapInstrumentIds introduce different verbs, and SearchBrokerCheck does not explicitly signal 'individual' unlike SearchBrokerCheckFirm, but the overall convention remains predictable.

Tool Count2/5

With 32 tools, the surface is quite heavy and exceeds the 25+ threshold for 'too many.' While the financial intelligence domain is broad, several search/detail pairs and overlapping data-source tools could be consolidated to reduce cognitive load for agents.

Completeness4/5

The toolset covers major workflows well: 13F holdings, fund fee comparison, advisor due diligence, macro data, price history, options, and identifier mapping. Minor gaps exist, such as no standalone real-time quote tool, no news/sentiment data, and no direct CUSIP-to-company-name search, but these are workable around.

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