dcf

## Preflight

Run the canonical pre-flight sequence — MCP health probe, ticker resolution, workspace `style.md` override, memory load, and coverage check. See `contracts/preflight.md`.

Include the `X-Agentii-Trace` header on every tool call per `contracts/x-agentii-trace-header.md`.
## Triggers

- analyze dcf model
- run dcf model analysis
- produce dcf model report
- dcf model breakdown
- dcf model deep dive
- build a dcf model
- assess dcf model
- quantify dcf model
- compare dcf model across peers
- review dcf model for
- generate dcf model on
- dcf model for investment decision

## Defaults

| Parameter | Default | Notes |
|---|---|---|
| lookback_years | 3 | Historical data window |
| include_peers | false | Whether to surface a peer comparison block |

## Methodology

### Retrieval Scope

This skill performs unstructured document search at scale across SEC filings (10-K, 10-Q, 8-K). The three-layer agent-use-ready retrieval protocol (Document Discovery → Page Map → Deep Read) applies to all unstructured document search at scale.

### Retrieval Strategy

See `contracts/retrieval.md` for the canonical decision tree; skill-specific retrieval detail is in `references/methodology.md`.

### Temporal Scope

Default: 12 fiscal quarters (max 20). Financial modeling: trailing 12 quarters (3 fiscal years) for long-range projection inputs.

### Tool Allowlist

See frontmatter `allowed_tools`.

### Protocol

Step-by-step execution detail is in `references/methodology.md`.

## Deliverable Chain

**Inputs** → **Build** → **Validate** → **Output** → **Next**

1. **Inputs**: resolved ticker + `search_xbrl_facts` (Income Statement, Balance Sheet, Cash Flow) + `get_company_financials` + `get_realtime_quote` for current price.
2. **Build**: write a self-contained Python script using `openpyxl` that creates the DCF workbook (projections, WACC, terminal value, sensitivity tables) per `## Output Structure`. Execute via `Bash: python3 script.py`. Verify the `.xlsx` exists. If `import openpyxl` fails, fall back to `.md` summary with `data_availability: degraded` (see `contracts/office-tooling.md`).
3. **Validate**: run LibreOffice recalc; audit `hardcoded_count == 0` for tagged cells per `## Validation Gates`; verify projection horizon ≥ 5 years, terminal growth < risk-free proxy.
4. **Output**: write the artifact path per `## Output File`. (Optional) render an executive-summary `.pptx` via `Bash`+`python-pptx`; convert `.xlsx → PDF` via LibreOffice.
5. **Next**: append to `agentii.md`; hand off to a downstream pitch/review skill if requested.

## Validation Gates

1. **projection horizon**: ≥ 5 years (10 years for secular-trends analysis). *If failed*: If < 5 years: refuse delivery, report actual horizon.
2. **terminal growth rate**: < risk-free rate proxy (current 10Y UST). *If failed*: If terminal_g ≥ rf: flag in assumptions section, note conservatism violation.
3. **WACC components**: WACC = (E/V × Ke) + (D/V × Kd × (1-T) with all components cited to source data. *If failed*: If components uncited: refuse delivery, list missing citations.
4. **hardcoded_count**: == 0 for all cells tagged projection|margin|discount_factor|pv|sensitivity per xlsx_audit output. *If failed*: If hardcoded_count > 0: per the hardcode gate, refuse delivery. Bounce back to analytical-subagent ONCE with audit report.
5. **calculation arc cross-validation **: cross-statement balancing verified against `gold.xbrl_calculations` weights — the DCF free-cash-flow projection and income statement structure MUST align with the filer's reported concept hierarchy. Call `get_statement_structure/{ticker}?statement_type=income_statement&include_calculations=true`. Flag discrepancies ≥1% as audit findings. *If failed*: If material discrepancy (≥1%): flag in audit findings, refuse delivery for discrepancies ≥5%. Tool-diversity is also tracked here: distinct MCP tools used MUST be ≥ `min_tool_diversity` (5); below that, flag as depth-insufficient in Coverage Gaps (a quality signal, not a delivery blocker).

## Tool Fallbacks

Per-tool failure modes and fallback actions are tabulated in `references/tool-fallbacks.md`.

## Output File

Write the final deliverable to `{ticker}/{YYYY-MM-DD_HHMM}_dcf_{affix}.md` .

## Output Structure

The deliverable is a structured markdown report written to the path in `## Output File`. Full section-by-section template (headings, tables, and field definitions) lives in `references/output-structure.md`. Required elements:

1. **Executive Summary** — headline conclusions (≤200 words).
2. **Core analysis sections** — per this skill's methodology and analyst modes.
3. **Data classification** — tag findings `[FACT]` / `[DEDUCTED]` / `[VIEW]` per `contracts/snapshot-synthesis.md`.
4. **Coverage Gaps & Citations** — inline `/v/` citations are PRIMARY (immediately after each fact); the bottom **Citations** section is a non-duplicative roll-up index.
5. **Output frontmatter** — emit the FR-090 structured block per `contracts/output-frontmatter-schema.md`.

**Citations & memory**: follow `contracts/citation-and-memory.md` — ≥1 citation per 200 words; every material fact, table row, and metric is immediately followed by its inline clickable `https://agentii.ai/v/{ticker}/{citation_id}/{N}` link; a bottom **Citations** section provides a non-duplicative roll-up index; the closing TUI reply includes a compact **Key Citations** list (headline 5–10 facts) of clickable `/v/` URLs; and append the run to `agentii.md` per `contracts/agentii-md-schema.md`.

## Memory & Snapshot

- **Memory load** (pre-flight): load prior workspace context for the ticker before retrieval — see `contracts/memory-load.md`.
- **Structured output frontmatter**: emit the FR-090 block (`key_metrics`, `conclusions`, `facts_count`, `deducted_count`, `views_count`, `citation_count`) per `contracts/output-frontmatter-schema.md`.
- **Snapshot synthesis**: after writing the deliverable, update the two-tier snapshot and classify findings as `[FACT]`/`[DEDUCTED]