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Persistent retrieval over Atlas's lawful financial literature corpus: investing canon, Canadian tax sources, official filings, research papers, and CC-licensed books. Grounds stock picks, tax strategy, and financial literacy explanations in cited source chunks.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
US/international payment compliance for Canadian sole proprietors and corporations. W-8BEN management (individual + entity), withholding tax recovery, 1099 interception, FX accounting (BoC noon rate), T1135 monitoring, Reg 105 contractor rules, multi-currency reconciliation. Prevents 30% backup withholding and $25/day T1135 penalties. CC-specific: Wise USD, Stripe, primary US retainer, Kraken.
Complete, populate and fill out 3-statement financial model templates (Income Statement, Balance Sheet, Cash Flow Statement) . Use when asked to fill out model templates, complete existing model frameworks, populate financial models with data, complete a partially filled IS/BS/CF framework, or link integrated financial statements within an existing template structure. Triggers include requests to fill in, complete, or populate a 3-statement model template
Container for skills synthesized at runtime by skill_synthesizer.py. Each child directory is a [NEW] skill with its own SKILL.md + metrics.json. Promoted to skills/<slug>/ after 3 successful uses (skill_metrics.py promote).
Build and maintain a calendar of upcoming catalysts across a coverage universe — earnings dates, conferences, product launches, regulatory decisions, and macro events. Helps prioritize attention and position ahead of events. Triggers on "catalyst calendar", "upcoming events", "what's coming up", "earnings calendar", "event calendar", or "catalyst tracker".
Prepare for client review meetings with portfolio performance summary, allocation analysis, talking points, and action items. Pulls together account data into a concise meeting-ready format. Use before quarterly reviews, annual checkups, or ad-hoc client meetings. Triggers on "client review", "meeting prep for [client]", "quarterly review", "prep for [client name]", or "client meeting".
Framework for building competitive landscape decks — market positioning, competitor deep-dives, comparative analysis, strategic synthesis. Use when the user asks for a competitive landscape, competitor analysis, peer comparison, market positioning assessment, strategic review, or investment memo deck. Also triggers on "who are the competitors to X", "benchmark X against peers", "build a market map", or any request to systematically evaluate competitive dynamics across an industry.
| name | financial-literacy-rag |
| description | Persistent retrieval over Atlas's lawful financial literature corpus: investing canon, Canadian tax sources, official filings, research papers, and CC-licensed books. Grounds stock picks, tax strategy, and financial literacy explanations in cited source chunks. |
| triggers | ["RAG","literature","financial literacy","source-grounded","bibliography","canon","investing books","tax sources","embedded literature","retrieval","citations","research corpus"] |
| tier | core |
| dependencies | ["financial-planning","accounting-advisor","portfolio-rebalancing"] |
Atlas uses this skill when a response, stock pick, tax strategy, or teaching moment should be grounded in the embedded literature corpus rather than memory alone.
| Need | Module | Command |
|---|---|---|
| Embed Atlas docs | research/rag_pipeline.py | python -m research.rag_pipeline ingest-default |
| Embed a licensed local file | research/rag_pipeline.py | python -m research.rag_pipeline ingest-path <file> --permission-status cc_licensed ... |
| Embed licensed inbox | research/rag_pipeline.py | python -m research.rag_pipeline ingest-inbox --tier cc_licensed --topic investing_canon |
| Embed an official/open URL | research/rag_pipeline.py | python -m research.rag_pipeline ingest-url <url> --permission-status open_access ... |
| Retrieve context | research/rag_pipeline.py | retrieve_literature_context(query, top_k=6) |
| Stock-pick grounding | research/stock_picker.py | Automatic inside StockPickerAgent.pick() and deep_dive() |
public_domain, official_public,
open_access, cc_licensed, or owned_or_licensed sources.permission_required or metadata_only.research/_data_integrity.py.If CC provides a lawful copy of a copyrighted book or course text, place it in
research/literature_inbox/ (git-ignored), then ingest it as:
python -m research.rag_pipeline ingest-path "path/to/book.pdf" \
--title "Book Title" \
--tier tier_1 \
--topic value_investing \
--year 1949 \
--permission-status cc_licensed \
--license-note "CC-provided lawful access; internal Atlas research use."
Do not fetch unofficial mirror PDFs. Use local files supplied by CC, official publisher portals, or public-domain/open-access sources.