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Discover comparable stock candidates

find_stock_peers
Read-only

Discover stock comparison candidates for a Bullrun ticker using stored industry or sector classification, returning compact multiples and growth plus ready-to-use compare arguments.

Instructions

Discover stock comparison candidates for one exact Bullrun ticker using stored industry or sector classification. Discloses the chosen classification, country preference, deterministic selection order, scan cap and issuer/listing exclusions. Excludes the subject, secondary listings and identifiable duplicate issuers/share classes. Returns compact stored multiples/growth plus ready-to-use compare_stocks arguments. Classification peers are not verified competitors or a financial-similarity ranking; no generated peers or paid graph discovery. Read-only.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum peers. compare_stocks supports the subject plus at most four selected peers.
tickerYesBullrun equity ticker, e.g. AAPL, BMW or 6324.T. Use the listing ticker returned by search_stocks. US/European examples: AAPL, BMW, NESN. Most Asian listings keep their exchange suffix (6324.T, 0700.HK); some use bare codes (005930). Native or suffixed forms resolve only when one listing matches; search by company name or ISIN if unsure.
matchByNoauto uses exact stored industry when present, otherwise sector. It does not silently widen an empty industry result to the entire sector.auto
sameCountryOnlyNoRestrict to the subject's exact stored country. Otherwise same-country candidates are shown first, followed by other countries.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.9.0
    • changedInput schema / properties / ticker / description
      Previous value: -"Bullrun equity ticker, e.g. AAPL, BMW or 6324.T. Bullrun tickers: US and most European listings use the plain local symbol (AAPL, BMW, NESN, ABBN); most Asian and Indian listings keep their exchange suffix (Tokyo 6324.T, Hong Kong 0700.HK, Shanghai 600519.SS, Shenzhen 000001.SZ, Taiwan 2330.TW, Korea 000100.KS, Singapore D05.SI, India RELIANCE.NS), but some Japanese and Korean large caps are plain codes (Toyota 7203, Samsung 005930). Either form is resolved automatically when exactly one listing matches; use search_stocks to find a ticker by company name or ISIN."New value: +"Bullrun equity ticker, e.g. AAPL, BMW or 6324.T. Use the listing ticker returned by search_stocks. US/European examples: AAPL, BMW, NESN. Most Asian listings keep their exchange suffix (6324.T, 0700.HK); some use bare codes (005930). Native or suffixed forms resolve only when one listing matches; search by company name or ISIN if unsure."
  2. Changed1 schema field changedv0.8.1
    • changedInput schema / properties / ticker / description
      Previous value: -"Exact native Bullrun equity ticker. Use search_stocks first for a company name, ISIN or Yahoo-format symbol."New value: +"Bullrun equity ticker, e.g. AAPL, BMW or 6324.T. Bullrun tickers: US and most European listings use the plain local symbol (AAPL, BMW, NESN, ABBN); most Asian and Indian listings keep their exchange suffix (Tokyo 6324.T, Hong Kong 0700.HK, Shanghai 600519.SS, Shenzhen 000001.SZ, Taiwan 2330.TW, Korea 000100.KS, Singapore D05.SI, India RELIANCE.NS), but some Japanese and Korean large caps are plain codes (Toyota 7203, Samsung 005930). Either form is resolved automatically when exactly one listing matches; use search_stocks to find a ticker by company name or ISIN."
  3. Addedv0.7.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already cover readOnly/destructive/openWorld, so the bar is lower, yet the description adds real context: deterministic selection order, a scan cap, issuer/listing exclusions, and disclosure of the chosen classification. It stops short of stating result volume or what happens when no industry or sector match exists beyond the matchBy note.

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-loaded with the core purpose, then scope, exclusions, and caveats in short declarative sentences. It is dense and jargon-heavy ('Bullrun ticker,' 'scan cap,' 'issuer/listing exclusions') for a four-parameter tool, but nearly every clause carries selection-relevant information.

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 still says what comes back: compact stored multiples/growth plus compare_stocks arguments. Combined with the coverage of selection order, exclusions, and classification caveats, an agent has enough to call it correctly and interpret results.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3; the description still adds meaning by framing sameCountryOnly as a preference-with-fallback ordering and matchBy as not widening an empty industry result. The 'compare_stocks supports the subject plus at most four selected peers' note reinforces limit semantics, though it does not restate the 1-10 range.

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 and resource: 'Discover stock comparison candidates for one exact Bullrun ticker using stored industry or sector classification.' It is clearly differentiated from the sibling compare_stocks, which it feeds rather than duplicates, and from screen_stocks by being a peer-discovery rather than a filter-scan tool.

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

Usage Guidelines5/5

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

Gives explicit boundaries: stored classification only, no generated peers, no paid graph discovery, and peers are 'not verified competitors or a financial-similarity ranking.' It also names the downstream step by saying it returns 'ready-to-use compare_stocks arguments,' which routes the agent to the correct sibling for actual comparison.

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