initiating-coverage

$npx mdskill add openai/role-specific-plugins/initiating-coverage

Generate public-equity initiating coverage reports

  • Creates formal initial analysis for new stock listings.
  • Depends on filings, earnings data, and market models.
  • Decides scope using source category plans and context.
  • Delivers structured output via the investing router.

SKILL.md

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---
name: initiating-coverage
description: Use when building public-equity-investing initiating coverage reports. Do not use for trade pitches, memos, earnings notes, models, or tearsheets.
---

# Initiating Coverage

## Skill Configuration

### User Context Preflight

Before searching connectors, retrieving evidence, or drafting output, run `python3 skills/user-context/scripts/user_context_preflight.py` with the shell working directory set to this plugin's root, and follow the returned `saved_context`, `source_category_plan`, and `next_action`. Set the working directory before the first attempt; do not probe alternate relative paths. Missing context must not block the requested workflow. Do not initialize state or run onboarding during ordinary workflow work.

If `next_action.id = "offer_orientation"` and the parent router has not already handled it, complete the requested work first and append its one-line optional setup offer once.

### Source Resolution

Load `../../shared/workflow-source-resolution.md`. Use `source_category_plan` lazily and attempt only the categories needed for this workflow: `company_filings_ir`, `earnings_transcripts_presentations`, `internal_research`, `portfolio_models_trackers`, and `market_data_estimates`.

## Internal Support

When this workflow needs rendering, evidence/data preparation, style, or sector context, route support through the visible `public-equity-investing` router and its bundled internal playbooks. Route workbook or model QA through the visible `model-audit-tieout` workflow.

## Deliverable Intake

Apply the presentation-surface precedence in `../../shared/deliverable-intake-policy.md`. This workflow's natural artifact is a polished standalone HTML initiation report. Do not choose chat-only output unless the user explicitly requests a lightweight response.

Before source gathering or analysis for a new standalone reader-facing hero deliverable, load `../../shared/deliverable-intake-policy.md` and use its adaptive `request_user_input` preflight for materially unresolved format, depth, audience/use, or focus choices. Reuse resolved preferences in downstream steps; when acting only as input to an owning workflow, do not re-prompt.

## Purpose

Build a full public-equity-investing initiation report that is thesis-led, model-backed, valuation-aware, source-disciplined, and explicit about what is proven versus assumed.

This skill owns initiation-style research architecture. It can produce a report outline, full initiation report, structured internal handoff, source request list, model/valuation workplan, or deck-ready storyboard. For a new standalone reader-facing initiation package, default to a polished standalone HTML initiation report following `../../shared/html-artifact-standard.md`, unless the user requests another surface, a quick/no-file answer, or a model/workbook-first deliverable. Use `dashboard-builder` only when the user explicitly asks for a standardized dashboard, reusable validated template, or structured payload-driven render. Structured JSON is support/audit material, not the final user-facing artifact. This skill does not own live trade expression, generic memo writing, earnings notes, model-only work, or one-page issuer profiles.

## Do Not Use

- Live trade pitch, pair trade, add/trim/exit rules, short-cover logic, or variant-perception trade expression: use `long-short-pitch`.
- IC memo, investment memo, committee note, client memo, PM update, or memo rewrite: use `memo-builder`.
- Pre-earnings or post-earnings note: use `earnings-preview` or `earnings-deep-dive`.
- Model refresh, DCF, 3-statement model, comps workbook, or sensitivity-only task: use the relevant model or scenario skill.
- One-page public issuer profile: use `company-tearsheet`.

## Non-Negotiables

- Preserve user files and models. Create additive outputs or marked-up recommendations unless the user explicitly asks for edits.
- Prioritize user-provided material, connected/approved sources, primary filings/releases/transcripts, trusted providers, then clearly labeled assumptions.
- Include report date, data cut-off, evidence confidence, underwriting status, unresolved conflicts, and major assumptions. Keep evidence confidence distinct from underwriting readiness; do not describe investability as source confidence.
- Label facts, company claims, street estimates, model-derived values, PM judgment, assumptions, mixed claims, and missing sources.
- Do not make personalized investment advice or compliance/legal/tax conclusions. Treat rating/target price language as research output requiring human review.
- If context is thin, produce a skeleton, research agenda, model architecture, source request list, and thesis hypotheses rather than fabricating facts.

## Workflow

1. **Classify the mode.** Choose `sell_side_initiation`, `buy_side_deep_dive`, `long_only_initiation`, `hedge_fund_initiation`, `credit_adjacent_initiation`, `sector_initiation`, `model_first_initiation`, or `report_refresh`. Load `references/report-modes.md` only when mode-specific requirements matter.
2. **Assess context depth.** For no-context prompts, ask one targeted clarification only if company/security or output mode is unclear. For partial/full context, preserve supplied facts, identify missing inputs, and build a source register and assumption register.
3. **Complete market data and valuation inputs.** Before finalizing a substantive initiation, retrieve current price with an as-of timestamp, market capitalization, diluted share-count inputs, enterprise-value inputs, and available consensus or estimate context from approved accessible sources. Load `references/source-and-evidence.md` for required treatment. If an input is unavailable, label it missing and explain what valuation conclusion it prevents; do not omit available market context simply because the report remains preliminary.
4. **Coordinate with local skills.** Use `financial-source-of-truth` for evidence posture, `company-tearsheet` for issuer baseline, `financials-normalizer` or `excel-data-cleaner` for source prep, model skills for valuation work, `scenario-sensitivity-generator` for cases, and `thesis-tracker` after initiation.
5. **Frame the senior thesis.** Answer what the market is missing, what must be true, what falsifies the thesis, which KPI/catalyst matters, why the valuation method fits, and what would change the view.
6. **Apply the financed-growth gate when material.** When capital intensity, debt, lease liabilities, dilution, customer-funded buildout, or financing risk is central to the equity debate, require a pro forma fully diluted capitalization / enterprise-value bridge and after-financing return evidence before a positive ownership conclusion or target price. Use normalized FCF, ROIC or return on invested capacity, capacity-cohort cash returns, leverage, and interest burden as applicable. Treat equity-value-to-revenue or other revenue multiples as preliminary market context only when material financed obligations are not yet incorporated.
7. **Build the report.** Default structure: cover/view, executive summary, key debates, company overview, industry position, model summary, valuation, catalysts, risks/disconfirmers, scenarios, and source appendix. In standalone HTML, make the first read a single research-posture block, the central debate, the valuation or capital-return gate, the essential evidence, and what remains missing. Do not repeat the same conclusion in a hero, metric tile, PM-answer block, and decision box.
8. **Apply sector context.** Load `references/sector-overlays.md` for report-mode framing and use `sector-context-overlay` only when sector nuance affects KPIs, valuation, or red flags.
9. **Run QA.** Confirm the report has a real view, falsifiable thesis, sourced metrics, visible data cut-off, source conflicts, appropriate sector metrics, and non-boilerplate risks. For a local HTML file, inspect the opening viewport and important downstream sections with local headless-browser screenshots rather than the in-app Browser plugin; iterate on hierarchy, clipping, citation noise, and readability.

## Sub-agent decomposition

For complex medium/large requests, use sub-agents where available; otherwise emulate the split as named workstreams. Suggested lanes: evidence gathering, company and industry analysis, model/valuation, thesis and risk, and report QA. Keep this skill as the lead: reconcile conflicts, source labels, assumptions, open items, final QA, and the user-facing answer.


## Artifact Contract

Default initiation output should include:

- MD / PM-level answer with recommendation or research posture.
- Investment thesis with 3-5 evidence-linked claims.
- Key debates and variant perception.
- Company and industry overview.
- Model and forecast driver table.
- Valuation / target price methodology, sensitivity, and backup method.
- Current market data and valuation-input status, including as-of time and explicit missing inputs.
- Earnings quality and EPS basis when P/E or EPS-driven valuation is used.
- Catalysts, risks, disconfirming evidence, and monitoring items.
- Source register, conflicts, assumptions, and open evidence requests.

For a long-only initiation where valuation, the capital stack, or after-financing cash economics remain materially unproven, label the output a `Preliminary initiation underwrite` or `Watchlist initiation`. State the evidence and modeling required before ownership rather than implying a completed positive initiation or supplying an unsupported target price. This posture does not excuse omitting current market data that is obtainable from approved accessible sources.

For standalone HTML artifacts, keep citations traceable but readable: do not fragment tickers, fiscal periods, dates, prices, ranges, multiples, or metric names with inline source links. Cite a complete figure or statement, or use a compact nearby source note.

Structured handoffs should follow `references/output-schema.md` and can be validated with:

```bash
python scripts/validate_initiation_json.py path/to/initiation.json
```

For publication-looking reports, run `python scripts/validate_initiation_json.py path/to/initiation.json --publication-ready` so unresolved placeholders, weak source metadata, and unknown source IDs hard-fail. Use the validated structure to render or support the human-readable report; do not make raw JSON the lead deliverable unless explicitly requested.

Use `scripts/calculate_price_target.py` only when valuation assumptions are available in JSON; the helper calculates math, not analyst judgment.

If the user explicitly asks for a standardized dashboard, use `references/DASHBOARD_PACK.md`. `initiating-coverage` owns the thesis, report architecture, and valuation judgment; `dashboard-builder` owns the shell/rendering/QA. Build a `public_equity_investing_dashboard.v1` payload as an internal renderer input, and keep JSON/Markdown/CSV support files behind the HTML dashboard unless explicitly requested.

## Reference Map

- `references/report-modes.md`: mode-specific output standards.
- `references/report-architecture.md`: full report structures and section variants.
- `references/thesis-framework.md`: senior thesis, debate, and falsification prompts.
- `references/valuation-and-modeling.md`: valuation methods, assumptions, and price-target logic.
- `references/source-and-evidence.md`: source hierarchy, labels, stale data, and evidence requests.
- `references/sector-overlays.md`: sector KPI, valuation, and red-flag overlays.
- `references/pm-md-standards.md`: quality bar for PM/MD-level initiations.
- `references/output-templates.md`: reusable report sections.
- `references/quality-checklist.md`: final QA.
- `references/integration-guide.md`: local handoff patterns.

## Final Note

End each initiation with evidence confidence, underwriting status, data cut-off, unresolved conflicts, major assumptions, and the recommended next handoff such as `thesis-tracker`, `equity-model-update`, `earnings-preview`, or `long-short-pitch`.

## Public Equity PM Judgment Layer

For substantial initiation work, load `shared/pm-judgment-heuristics.md` before finalizing. Audience modes: `long_only_pm`, `long_short_hf`, `sell_side_research`, `etf_index_diligence`, `public_equity_diligence`.

Required PM judgment:
- State the decision hinge, variant perception, what is priced in, valuation basis, downside mechanism, ownership/positioning, benchmark relevance, and falsifiers.
- Add `etf_index_constituent_diligence` when the user is assessing an issuer as an ETF/index constituent, index exposure, passive-flow risk, or benchmark-relative holding.
- Include market cap, float/liquidity, ownership, short interest, factor exposure, index membership, and capital allocation when source-backed or clearly missing.
- Fund/product diligence is out of scope; public issuer or constituent diligence is in scope.

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