Dcf Model Builder

DCF Model Builder

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.

Deliverable Intake

Apply the presentation-surface precedence in ../../shared/deliverable-intake-policy.md. This workflow's natural artifact is an XLSX DCF valuation workbook. 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.

Own DCF-specific valuation builds: FCFF/FCFE method choice, WACC or cost of equity, terminal value, EV-to-equity bridge, per-share value, valuation sensitivities, QA checks, and a formula-first XLSX workbook.

Hard Contract

• Default model-build artifact level is banker_formula_workbook; use the formula workbook path for normal public-equity DCF build, refresh, valuation, and model-package requests.
• Formula mode is executed through scripts/build_banker_formula_workbook.py and must be labeled banker_formula_workbook only when its run log, workbook inspection, and model_citations.json prove the formula builder ran successfully.
• Deterministic scripts remain available for controlled computed values, smoke tests, or explicit lightweight support exports. They produce output/model.xlsx, output/plan.json, output/run_log.json, optional support note output/support_note.md, and output/manifest.json. Legacy output/report.md is written only with --write-report-md.
• Formula scripts produce banker_formula_workbook.xlsx, banker_formula_workbook_run_log.json, model_citations.json, and manifest.json in the selected output directory. The workbook is the hero deliverable; citation JSON, run logs, and manifests are support artifacts.
• Formula and deterministic workbooks must start with a Cover tab that functions as an investment landing page: issuer, current price versus implied value, valuation range, case outputs, DCF bridge, WACC/terminal assumptions, sensitivity drivers, source posture, warnings/hard failures, and workbook map.
• run_log.json and manifest.json are required reliability artifacts; hard failures force not-decision-ready.
• Never delete, overwrite, or mutate source data unless explicitly requested. Write new outputs under output/ or a clearly named copy.
• Keep material inputs source-labeled: reported, company_guidance, consensus, management_case, user_provided, connected_app, web_research, analyst_estimate, placeholder, or derived.
• If placeholders, stale data, unsupported WACC, missing share count/net debt, or weak analyst estimates drive value, mark the output no higher than screen-grade.

Routing

Use this skill when the deliverable is a DCF build, refresh, rerun, valuation sensitivity, reverse DCF, or DCF model package. Route away when the primary ask is workbook audit/debug (model-audit-tieout), source hierarchy (financial-source-of-truth), raw financial normalization (financials-normalizer), raw spreadsheet cleanup (excel-data-cleaner), expanded stress architecture (scenario-sensitivity-generator), trading comps (comps-valuation), or memo/deck polish.

For complex tasks, split the work into source-of-truth, accounting normalization, operating forecast, cost of capital, terminal value/ROIC, scenario valuation, and audit workstreams. If sub-agents are unavailable, emulate those workstreams explicitly before running the pipeline.

When To Invoke Support

Load shared/support-layer-routing-contract.md when source/data/QC/style support is needed. Use financial-source-of-truth before relying on load-bearing market data, filings, guidance, consensus, share count, net debt, WACC, or terminal assumptions. Use financials-normalizer before plan creation when historical financials, KPI schedules, segment data, guidance, consensus/provider exports, share count, net debt, or capital allocation inputs are messy. Use excel-data-cleaner before importing malformed tables. Use model-audit-tieout for formula integrity, external links, recalc/cache posture, and final tie-out; use deck-report-qc only for circulation packs. Support artifacts stay secondary to the formula workbook or HTML report.

Input Handling

• Preferred input is a plan.json matching the schema.
• No context: run assets/plan_template.json only as illustrative and label placeholders.
• Named company with no data: gather connected/public data when allowed; otherwise ask targeted questions or build a caveated screen-grade plan.
• Partial context: preserve user assumptions, fill only non-economic structure when obvious, and label gaps.
• Full plan: validate first; do not silently change conclusion-driving assumptions.
• When the investment question turns on an operating KPI such as bookings, GBV, take rate, volumes, users, units, or retention, load references/industry-playbooks.md and build from the sector-relevant driver where the workbook supports it. If formula mode cannot represent that driver schedule, disclose the proxy prominently on the Cover or Executive Summary and in Source Notes, and keep the model no higher than screen-grade; do not silently substitute a generic revenue CAGR.

Required Workflow

1. Create or identify a valid plan.json.
2. Validate with python3 scripts/validate_plan.py path/to/plan.json.
3. Default path: execute python3 scripts/build_banker_formula_workbook.py path/to/plan.json --output-dir output and inspect banker_formula_workbook_run_log.json.
4. Use python3 scripts/run_pipeline.py path/to/plan.json only for controlled computed values, smoke tests, explicit lightweight support exports, or when formula mode fails and the fallback is clearly labeled deterministic_export.
5. Review the relevant run log for hard failures, warnings, checks, source basis, workbook inspection, and P0/model handoff.
6. Render and visually inspect the generated workbook before delivery. Confirm that template example data is absent from a named-company model, actual/estimate periods align across tabs, core outputs and sources are legible, and checks disclose any unsupported driver or roll-forward.
7. Deliver the workbook as the hero artifact and link the normalized plan, run log, manifest, citation ledger, and optional support note as audit files.

Smoke test:

python3 scripts/validate_plan.py assets/plan_template.json
python3 scripts/build_banker_formula_workbook.py assets/plan_template.json --output-dir /private/tmp/public-equity-investing-dcf-formula
python3 scripts/run_pipeline.py assets/plan_template.json

Formula Mode Guardrail

Load references/banker-formula-workbook-contract.md before using formula mode. If the formula builder fails, the template is missing, required tabs/formulas/styles are not present, external links appear, or model_citations.json is absent, do not describe any fallback artifact as a banker formula workbook.

Status Labels

Use exactly: decision-grade, senior-review-ready, screen-grade, not-decision-ready, blocked. Use blocked only before a run log exists; after execution, hard failures mean not-decision-ready.

Deferred Reference Router

Load references/reference-router.md only when deeper schema, math, QA, integration, sector, or senior valuation judgment guidance is needed. The router preserves the detailed reference map without loading every reference during invocation.

Equity Valuation PM Standard

Load shared/equity-valuation-pm-standard.md and shared/pm-judgment-heuristics.md for substantial model, valuation, scenario, model-update, or audit work.

The output must state what the current stock price implies, the variant estimate path, whether upside is driven by fundamentals, multiple expansion, mix, capital return, sentiment, or event probability, what breaks first in downside, what changes target, rating, sizing, hedge, trim, exit, or watchlist status, and what evidence is missing.

Keep equity valuation as the center of gravity. Debt is allowed only as an input to common-equity value through net debt, cost of debt, leverage, liquidity, refinancing risk, or downside equity impairment. Use Credit Markets for bond comps, loan comps, CDS, spread/yield relative value, covenant-package analysis, debt-security valuation, recovery waterfall, restructuring valuation, creditworthiness, private-credit / public-credit instrument underwriting, or distressed claim valuation.

Source & license

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

• Author: spacemata
• Source: spacemata/codex-plugins-for-claude-code
• License: MIT

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