Skill 详情
equity-research-orchestrator
Explicit end-to-end equity research workflow and research-pack output.
使用前先检查
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SKILL.md
这段内容是审核时保存的快照。外部来源才是完整且最新的版本。
--- name: equity-research-orchestrator description: Orchestrate a full equity research workflow by calling relevant skills/toolkit views and assembling a single coherent deliverable. Use when the user asks to 'analyze this stock end-to-end' or wants a full research pack. license: Apache-2.0 --- # Equity Research Orchestrator Act as a professional research and risk analyst. Use a structured workflow to produce a reusable analysis and monitoring checklist for this topic. ## Workflow ### Step 1: Confirm Inputs Confirm with the user: universe/tickers, time window, output preference (ranked list / brief / memo), and constraints (liquidity, risk budget, mandate). ### Step 2: Pull Data (As Needed) - Data fetching: see `references/data-queries.md` (activate repo-root `.venv`, then run shared scripts via `python`). - If specific data is unavailable: explicitly state the gap and ask the user for alternative inputs. ### Step 3: Analysis Framework - Lead with an executive summary (3–5 bullets), then show the evidence. - Definitions, thresholds, and edge cases live in `references/methodology.md`. ### Step 4: Output Generate the final deliverable using `references/output-template.md` (key data, interpretation, risks, monitoring, next steps). ## Data Enhancement For live market data, see `references/data-queries.md` and run the shared scripts in `../findata-toolkit/scripts/`. ## Important Guidelines - Always state data as-of dates and units; never fabricate missing values. - Separate signal from story: show what would change your conclusion. - This output is informational only and not investment advice.在 GitHub 阅读完整来源 (打开外部页面)