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 | |---|---|---| | lookbackyears | 3 | Historical data window | | includepeers | 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 0: per the hardcode gate, refuse delivery. Bounce back to analytical-subagent ONCE with audit report.
4. 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]/[VIEW] — see contracts/snapshot-synthesis.md.
• Session archival: record the run under sessions/{YYYY-MM-DD}/ and update sessions/INDEX.md per contracts/session-format.md.

Final Summary (TUI)

End the closing chat reply with a compact Key Citations list (headline 5–10 facts), each a clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link, so the user can cmd+click straight to the exact SEC page. See contracts/citation-and-memory.md.

Error Handling

| Failure Mode | Detection | Action | User-Facing Message | |---|---|---|---| | Missing data | Data API returns empty result set | Widen date range and retry once | "No data available for {ticker} in requested window." | | Partial data | Data API returns <80% expected records | Proceed with coverage gaps section | "Analysis based on partial data; see Coverage Gaps section." | | Sector mismatch | Peer sector != target sector | Filter out mismatched peers | "Removed {n} peer(s) due to sector mismatch." | | Insufficient history | Ticker <3 years on public markets | Downgrade to limited-history profile | "Limited historical data; analysis adjusted accordingly." | | MCP unreachable | Preflight probe fails | Halt with actionable error | "agentii data plane unreachable; check connection." |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: agentii-ai
• Source: agentii-ai/agentii-investment-intelligence
• License: Apache-2.0
• Homepage: https://agentii.ai

Install and usage instructions live in the source repository linked above.