stock-research

name	Stock Research
description	Canonical Hone security-research skill covering company and ETF/fund analysis, valuation framing, and criteria-based screening
when_to_use	Use when the user wants company or ETF/fund research, valuation framing, or a small security shortlist based on explicit criteria
user-invocable	true
context	inline
aliases	["stock research","valuation","stock screener","stock selection","OWGZ","OWXG"]
allowed-tools	["data_fetch","web_search"]

Stock Research Skill

This is the canonical security-research entrypoint for Hone.

Use it for three closely related user intents:

1. Single-company or ETF/fund research
2. Valuation framing for a named company
3. Criteria-based stock screening that returns a short comparison list

Prefer keeping these modes inside one skill so the model does not have to choose between overlapping prompt variants.

Tool Guide

Tool call	Purpose
data_fetch(data_type="search", query="company name, alias, or ticker")	Mandatory entity-resolution step before company/security analysis
data_fetch(data_type="snapshot", ticker="ticker")	Recommended. Fetch a snapshot with price action plus company overview
data_fetch(data_type="earnings_outlook", ticker="ticker")	Preferred for a named security's earnings preview; includes quote, profile, earnings, estimates, targets, ratings, financials, coverage, and current-listing evidence
data_fetch(data_type="quote", ticker="ticker")	Fetch detailed latest-available quote data such as price, change, volume, and provider timestamp
data_fetch(data_type="profile", ticker="ticker")	Fetch company details such as business description, industry, and CEO
data_fetch(data_type="financials", ticker="ticker")	Fetch financial statements or valuation-relevant fundamentals
data_fetch(data_type="etf_holdings", ticker="ticker")	Fetch ETF/fund holdings after profile confirms isEtf or isFund
data_fetch(data_type="news", ticker="ticker")	Fetch current-turn news for the exact security
data_fetch(data_type="gainers_losers")	Broader market scan when a screening request needs candidates
data_fetch(data_type="sector_performance")	Sector strength context for screening or relative positioning
web_search(query="...")	Search for news, analyst views, and recent events

Adapt To The Requested Outcome

Read the complete request and choose the evidence and answer shape that best fits it; these are reusable answer patterns, not a closed intent classifier or a grammar that the user's wording must match:

• Research mode: the user asks about one company, ETF/fund, ticker, fundamentals, technicals, or recent developments
• Valuation mode: the user asks whether a company looks rich, cheap, stretched, fairly priced, or wants a valuation bridge / peer view
• Screening mode: the user asks for a shortlist that matches factors such as AI, dividend yield, value, growth, or momentum

Non-negotiable Current-turn Pipeline

1. In the main agent loop, read the complete current user query and retain every possible named security before answering. Treat any pre-scanned ticker as a candidate seed, never as proof that the entity set is complete. Do not rely on a service-side grammar that splits natural language on commas, and, 和, &, or /; names and symbols such as AT&T, S&P Global, BRK/B, and Berkshire Hathaway, Class B must remain understandable in context. Assign each named security one stable, distinct, case-sensitive entity_route key for this run and reuse it verbatim. Start with one batch/parallel discovery round using one separate data_fetch(data_type="search", query="...", entity_route="...", identity_match="...") call per named security; this tool-enabled round returns only tool calls, never a data-time line, summary, draft, or final prose. Calls may run in parallel, but never combine multiple securities into one query. identity_match is call-scoped and must be present on every search: set identity_match="exact_symbol" when the query is a ticker and identity_match="name_or_alias" when it is a company name, Chinese name, or alias. A previous declaration does not authorize a later search, and the service must not guess from case, length, or punctuation. Reuse the exact same route key on that security's refinement, quote, profile/snapshot, and later DataFetch calls. An exact-symbol route keeps its symbol constraint even during a later company-name refinement, with only bounded provider separator equivalence such as BRK/B, BRK-B, and BRK.B; an ETF or product whose name merely embeds CRWV cannot replace CRWV. The key is internal evidence linkage, not a user-visible entity claim. If a Chinese name or alias search is empty, refine it within the same route and use refines_query to copy the original empty query verbatim with matching case. If an earlier search omitted the route key, repeat its exact query or set supersedes_query to that old query verbatim with matching case so at most that one provisional route is migrated; never guess alias equivalence or erase another entity's gap. refines_query and supersedes_query are strictly mutually exclusive: provide at most one on any search, because providing both invalidates that identity search and leaves the route pending. After search results return, select one standard symbol per route and give that same symbol both quote and profile/asset-route coverage. A plain ticker such as NBIS, , , or is normal user input: query it directly instead of asking for a company name. Only ask for clarification after current-turn tools still show genuine ambiguity or no authoritative coverage.

Research Mode

1. Resolve every named security discovered from the complete current query with current-turn tools, preferably in one batch/parallel first round. A ticker is a first-class search input but becomes an entity only after exact-symbol confirmation; names, aliases, Chinese names, multiple securities, and share classes must all produce explicit resolution results. A pre-scan miss must fall through to this agent loop, not become a user-facing failure. Never take the first approximate result silently, and clarify only when tool evidence remains genuinely ambiguous.
2. Verify the current-turn same-symbol quote, then select the route from structured exact-symbol evidence. A company uses profile, financials, and news; an ETF/fund confirmed by profile isEtf/isFund uses etf_holdings and news; a crypto asset confirmed by exact search market evidence such as exchangeShortName=CRYPTO uses the same-symbol quote and relevant news. Never request corporate financials or an earnings calendar for a confirmed ETF/fund, and never request corporate financials, an earnings calendar, or ETF holdings for crypto. Treat provider errors separately from a successful empty response. Do not infer an asset type from an empty response.
3. A quote-only question may stay concise. A deep single-company, quarter-outlook, “can it take off”, fundamentals, valuation, or buyability question must use these nine numbered sections in order:
   1. Conclusion
   2. What the company is and how it makes money
   3. Moat and competitive barriers
   4. Industry position and key competitors
   5. Financial quality
   6. Valuation using at least two suitable methods only when the current-turn inputs are complete; otherwise use the method that can be calculated rigorously and state the missing inputs
   7. Bull / Bear / Base Case
   8. Catalysts, risks, and falsification conditions
   9. Action: buy / wait / reduce / sell / observe, with triggers
4. Preserve the Agent-authored first-line data timestamp and quote basis, and distinguish verified facts, inference, conclusion, and action. Do not ask for the user's cost basis as a substitute for completing the analysis.
5. If required live evidence is missing or mismatched, stop numeric conclusions instead of filling gaps from memory, history, profiles, or another symbol.
6. If the user explicitly asks for a chart, trend line, comparison visual, or the answer would be materially clearer as a chart, hand off to chart_visualization with the concrete numbers you already fetched.

If the exact quote and profile are valid but current company financial statements are empty, failed, mismatched, or limited to an income statement, do not fail the whole response and do not fabricate values. Keep all nine sections, state 本轮公司财务数据未核验 in section 5 with the exact missing scope, and base the remaining sections only on verified quote/profile/news evidence. An income statement does not prove cash, debt, net debt, or free cash flow. Financial-data absence must never be rewritten as an absence of current quote capability.

ETF / Fund Research Route

When the exact-symbol profile confirms isEtf=true or isFund=true, use these nine numbered sections instead of the company template:

1. Conclusion
2. Fund objective, strategy, and tracked exposure
3. Holdings, concentration, and primary exposures
4. Geographic, sector, and currency risk
5. Liquidity, fund size, and trading characteristics
6. Fees, tracking error, and underlying-asset valuation framing
7. Bull / Bear / Base Case
8. Catalysts, risks, and falsification conditions
9. Action: buy / wait / reduce / sell / observe, with triggers

Preserve the Agent-authored first-line data timestamp and quote basis, and separate verified facts from inference and action. If holdings, fees, size, or tracking-error evidence is absent, label that item as not verified in the current turn; do not fill it from memory. A successful empty company financial response for a confirmed ETF/fund is not a provider outage and must not block this route.

Crypto Research Route

Only classify crypto from exact-symbol structured market evidence such as exchangeShortName=CRYPTO; do not infer it from a USD suffix. A confirmed crypto asset uses quote and relevant news, not stock profile, company financials, an earnings calendar, or ETF holdings. Use nine substantive numbered sections: conclusion with verified current price; asset/network/use case; supply/tokenomics/concentration; adoption/liquidity/market structure; on-chain/network/ecosystem evidence; valuation framework and assumptions; Bull/Bear/Base; catalysts/regulation/risks/falsification; and an action with trigger conditions. Label absent on-chain, supply, or ecosystem evidence as not verified in the current turn.

Valuation Mode

1. Resolve the ticker first, fetch the same-symbol quote, and read the exact-symbol profile; do not attempt valuation before confirming whether the entity is a company or an ETF/fund.
2. For a company, fetch financials; add quote or snapshot if you also need current market context. Use at least two suitable methods only when every numerator, denominator, period, and balance-sheet input is present. Annual FY revenue is not TTM. Without verified cash/debt or enterprise value, label market-cap/EBITDA as such and never call it EV/EBITDA. If only one method is fully supported, use that method, disclose the missing inputs, and do not invent net debt, historical multiples, target prices, or technical support levels to fill the template.
3. For an ETF/fund confirmed by isEtf/isFund, fetch etf_holdings plus quote and frame valuation through underlying holdings/exposures, fees, tracking error, concentration, and applicable portfolio-level multiples. Do not fetch corporate financials or an earnings calendar, and do not apply a single-company DCF to the fund itself.
4. Use web_search for the latest operating updates, strategy changes, holdings disclosures, guidance changes, or peer-comparison context appropriate to the confirmed asset type.
5. Do not collapse the result into a simplistic categorical verdict with no assumptions attached.

Screening Mode

1. Extract the user's explicit criteria before naming companies
2. Use gainers_losers, sector_performance, or targeted web_search to form an initial candidate set
3. Narrow the result to 3-5 names, exact-resolve every final candidate, and fetch a same-symbol snapshot or quote for each
4. Return a comparison shortlist with why each name matches the screen, plus the main risk or diligence gap for each one
5. Do not output a blunt recommendation list without comparison logic or caveats