| .. | ||
| forensic-analysis-example.md | ||
| README.md | ||
| standard-analysis-example.md | ||
Worked examples — gold-standard reference analyses
These are illustrative exemplars: complete analyses the skill is meant to
produce, written so a new run can see the target quality rather than infer it
from the template alone. Read them alongside references/12-report-template.md
(structure) — the template shows the shape, these show the bar.
Every company here is fictional and every figure is invented. That is
deliberate: it lets the numbers be internally consistent and freely shown
without any risk of presenting fabricated data about a real company as if it
were sourced. In a real analysis the same citations ([FY26 AR, p.112]) must
point at real documents, and the non-negotiables — never invent a number,
document-first sourcing, the recency gate — apply in full. Do not lift any
figure from these files into a real analysis.
| File | Mode | What it demonstrates |
|---|---|---|
standard-analysis-example.md |
Standard | The full workflow on a (fictional) FMCG franchise: sector playbook and suppressed metrics, DuPont, working-capital and cash-conversion analysis, a document-sourced data-quality note with source tiers, a sector-relative scorecard with the gate disclosure, valuation.py output (EV bridge, trailing multiples, reverse-DCF implied growth, scenario table), a genuine bear case, and observable invalidation triggers. Passes scripts/lint_report.py. |
forensic-analysis-example.md |
Forensic | A forensic read of the evals/fixtures/synthetic-ar-excerpt.md extracts (fictional Kesar Agro): the F0–F5 runbook, the accruals and proof-of-cash tests, the CARO and related-party evidence, and a "can these accounts bear weight?" verdict that stops short of valuation on purpose. |
Both were checked with the bundled gates: the standard example passes
python scripts/lint_report.py, and its valuation section is the verbatim output
of python scripts/valuation.py on the same inputs.