| name | Stock Research |
| description | Canonical Hone equity-research skill covering single-stock analysis, valuation framing, and criteria-based screening |
| when_to_use | Use when the user wants company research, valuation framing, or a small stock 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","skill_tool"] |
Stock Research Skill
This is the canonical equity-research entrypoint for Hone.
Use it for three closely related user intents:
- Single-company research
- Valuation framing for a named company
- 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="snapshot", symbol="ticker") | Recommended. Fetch a snapshot with price action plus company overview |
data_fetch(data_type="quote", symbol="ticker") | Fetch detailed real-time quote data such as price, change, and volume |
data_fetch(data_type="profile", symbol="ticker") | Fetch company details such as business description, industry, and CEO |
data_fetch(data_type="financials", symbol="ticker") | Fetch financial statements or valuation-relevant fundamentals |
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 |
Mode Selection
Choose the mode from the user's request before fetching data:
- Research mode: the user asks about one company, 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
Research Mode
- Identify the ticker mentioned by the user. If it is unclear, search first with
data_fetch(data_type="search", symbol="...")
- Call
snapshot for the baseline data
- Decide whether to add
web_search for news or causes
- Output a combined answer covering price action, fundamentals, recent events, and risks
- 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
Valuation Mode
- Resolve the ticker first; do not attempt valuation without confirming the company
- Fetch
financials; add quote or snapshot if you also need current market context
- Use
web_search for the latest operating updates, guidance changes, or peer-comparison context
- Explain the valuation through assumptions, peer multiples, and business quality, and state which conditions would make the company look richer, more balanced, or more compelling relative to peers
- Do not collapse the result into a simplistic categorical verdict with no assumptions attached
Screening Mode
- Extract the user's explicit criteria before naming companies
- Use
gainers_losers, sector_performance, or targeted web_search to form an initial candidate set
- Narrow the result to 3-5 names and fetch
snapshot for each final candidate
- Return a comparison shortlist with why each name matches the screen, plus the main risk or diligence gap for each one
- Do not output a blunt recommendation list without comparison logic or caveats
