Fintel Discovery — Financial Intelligence for AI Agents

Map Instrument IDs via OpenFIGI

MapInstrumentIds

Read-onlyIdempotent

    Map financial instrument identifiers between different ID systems using
    Bloomberg's OpenFIGI service. Converts between ticker symbols, ISINs,
    CUSIPs, and FIGIs in a single call.

    Use this tool when:
    - You have a ticker and need the ISIN or CUSIP (or vice versa)
    - You are normalizing instrument IDs when combining data from EDGAR,
      Yahoo Finance, and other sources that use different ID schemes
    - You need to identify what exchange a security trades on

    Supported idType values:
    - 'TICKER': Stock ticker symbol (e.g. 'AAPL')
    - 'ID_ISIN': ISIN (e.g. 'US0378331005')
    - 'ID_CUSIP': CUSIP (e.g. '037833100')
    - 'ID_FIGI': Bloomberg FIGI

    Include 'exchCode': 'US' to target US exchanges for ticker lookups.

    Source: Bloomberg OpenFIGI API. No API key required (optional key raises rate limits).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`params`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already mark the tool as readOnly, idempotent, and non-destructive, and the description adds meaningful behavioral context beyond that: it depends on Bloomberg's OpenFIGI API, requires no API key, and mentions optional keys affect rate limits. This gives an agent useful operational expectations that structured annotations alone do not provide.

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 well-structured with a clear intro, a bulleted 'Use this tool when' list, a compact table of supported idTypes, a targeted usage tip, and a source/authentication note. Every sentence serves a purpose and the most important information is front-loaded.

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

Completeness4/5

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

For a tool with an output schema, the description does not need to explain return values, and it adequately covers the core mapping use cases, supported identifiers, exchange targeting, and API source. It loses a point because it does not fully align with the schema's wider set of idType values and leaves the several non-OpenFIGI params unaddressed, which could confuse an agent trying to decide whether they matter.

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?

Given the reported 0% schema description coverage, the description needed to compensate, and it does explain the main idType values and exchCode usage with examples. However, it lists only four of the six idType options that appear in the schema (omitting ID_COMMON and ID_WERTPAPIER) and does not explain other mapping fields like micCode, currency, or securityType, nor the generic extra params such as wholesaler_ids and source_resource_id.

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 clearly states a specific verb and resource: 'Map financial instrument identifiers... using Bloomberg's OpenFIGI service' and explicitly says it converts between ticker symbols, ISINs, CUSIPs, and FIGIs. This distinguishes it from sibling search tools like SearchFigiInstruments and LookupTicker, which focus on lookup rather than cross-system ID conversion.

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 a dedicated 'Use this tool when' section with concrete scenarios: converting ticker to ISIN/CUSIP, normalizing IDs across data sources, and identifying exchanges. It gives actionable guidance like including 'exchCode': 'US' for ticker lookups, but it does not explicitly name sibling tools or describe when not to use it, so it stops short of a full 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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