القائمة
Extract structured fields from the bundled filing, write a grounded summary, grade it, and save a report. Usage /summarize
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Value a public company's equity end-to-end (FCFE at CAPM cost of equity) with an IB deal team — multi-year EDGAR data, scenario forecasting, Monte-Carlo DCF, dual-source comps, a verification gate, and an investment-committee sign-off. Run `/valuation <cik|ticker>`.
Value a public company end-to-end from its CIK or ticker. Run `/valuation <cik|ticker>`. Orchestrates EDGAR fetch, three parallel valuation lanes (Monte-Carlo DCF, dual-source comparables, qualitative/risk), and reconciliation into a fair-value median + P10–P90, benchmarked against the real market price.
Generate a professional 2-page report on a publicly-traded company as a self-contained HTML website. Given a company name, orchestrates five subagents in order (Generalist, Data Retriever, Data Scientist, Financial Analyst, Report Writer) — pulling the latest 10-K from SEC EDGAR, cleaning the financials, analyzing them, and writing the report. Use when the user asks for a company report, equity write-up, or 10-K-based analysis. Triggers include "write a report on <company>", "company report for <X>", "/company-report".
One sentence on what this command does and when to invoke it. Usage /my-skill "<arg>"
Answer a question about the bundled NovaCorp filings, grounded and graded. Usage /ask "<question>"
Route a research question, gather grounded evidence, and write a cited brief. Usage /brief "<question>"
| name | summarize |
| description | Extract structured fields from the bundled filing, write a grounded summary, grade it, and save a report. Usage /summarize |
Run the full Extract → Summarize → Grade → Check loop and save a report.
python -m tools.extract > reports/_fields.json
If schema_errors is non-empty, stop and report — do not summarize an invalid extraction.reports/_fields.json,
citing the field name behind every figure, and save it to reports/_summary.txt.python -m tools.grade --summary-file reports/_summary.txtfigure_coverage < 1.0, remove or correct the unsupported_figures and
re-grade; if faithfulness < 0.7, tighten the summary to the extracted fields. Loop at
most 3 times.reports/summary.md:
Try this to start:
/summarize → summarises the bundled Orion Dynamics Q3 FY2025 release.To see the faithfulness check bite, make the summarizer state a figure that is not in
reports/_fields.json (e.g. revenue of $2.30 billion) and re-grade: figure_coverage
drops below 1.0 and the loop sends it back.