Update to BeliefState

{
  "description": "Explain available BeliefState research about a company or ETF, from a beginner's overview to an analyst brief with investor views, catalysts, risks and cited cases. Use for company or fund research, not bulk financial-statement feeds or portfolio management.",
  "included_files": [],
  "name": "research-a-company-or-etf",
  "skill_md_contents": "---\nname: research-a-company-or-etf\ndescription: Explain available BeliefState research about a company or ETF, from a beginner's overview to an analyst brief with investor views, catalysts, risks and cited cases. Use for company or fund research, not bulk financial-statement feeds or portfolio management.\n---\n\n# Research a company or ETF\n\nHelp the user understand the available research at the level they requested. Reuse adequate conversation records before making another metered read.\n\n- Resolve the requested company, ETF or subject before retrieving research. Ask which investment when none was given. Use `search_companies` to resolve an ambiguous company name; use returned identifiers and clarify multiple listings rather than guessing. Use `search_entities` when a released non-company subject is the intended target.\n- Start ordinary company or ETF research with `get_brief`, using the default or `detail=overview` supported by the connected schema. Do not assume `detail=current` or brief cursors are published on every client. Do not request a full export when an overview answers the question.\n- For an ETF ticker, try its brief rather than treating absence from a direct-company coverage directory as proof that ETF research is unsupported. Explain the date of fund holdings, available constituent-company research, omitted holdings and coverage limits. Do not imply a complete thesis about every fund or its constituents.\n- Lead with what the available attributed views say, why those investors hold them, material catalysts and risks, and the source dates. Separate investor views, issuer/market context, engine assessments and your own synthesis. Date prices and preserve stale or missing context.\n- Open requested complete cases with `get_belief`. Use `get_belief_risks` or `get_belief_catalysts` for a requested object-level investigation, with exactly one supported subject scope. Preserve citations and unknown conditions; a combined summary is not multiple independent records.\n- Keep the answer useful for learning about a business, preparing an analyst brief, examining a sector exposure or building an evidence packet. Let the customer's AI apply personal goals and preferences. State when the library cannot support a requested conclusion instead of supplementing it with invented research.\n- Refresh market data only when the user requests a refresh and the available tool supports the subject. Historical questions retain their `as_of` cutoff and never become a current-data refresh. For what was known by a past date, use recorded availability and observation dates as well as publication; later discovery cannot be backdated into earlier knowledge.\n\nKeep goals, holdings, position sizes, risk preferences and conversation history in the customer's AI. Send only bounded public research selectors and a short public research goal as tool `context`, never private portfolio/account details, credentials or source bodies. Supply required model metadata truthfully. Make the first call serial, then reuse the server's exact `conversation_id` unchanged, including across follow-up requests. Preserve returned IDs, citations, coverage, omissions, dates and nulls. Use connected schemas and returned continuations rather than unpublished tools. Research can consume allowance or prepaid credit; explain the returned access/provider error and recovery guidance without fabricated results or repeated paid retries.\n"
}