Deep-Company Series: An 8-Part Deep Dive on One Company
Write an 8-part deep-dive series (~120k words total) on a single company, from cognitive reset to a decision framework. The core IP is not "writing well" but "revising strictly" — most finance long-form violates this skill's fact-check standard.
1. When to Use
The user wants "textbook-level" deep research on a company, published as a series of long-form articles. Distinct from a single research report:
- 8 parts, ~120k words, full loop from cognitive reset to a decision framework
- Each part stands alone (shareable singly) but shares one valuation / management / price framework
- Written for readers willing to spend 90 minutes understanding one company
Not for: a single research report, earnings note, sector study — use other skills (fundamentals / earnings / sector).
2. Series Template (8 Parts)
| # |
Title template |
Core question |
Words |
| 01 |
You think you understand X — you don't |
Cognitive reset: break 3 common illusions |
4,000-5,000 |
| 02 |
X's moat — {one-line business essence} |
Is the moat deep; will it be there in 5/10 years |
6,000-8,000 |
| 03 |
X's biggest profit engine — {most profitable business} |
What is the core business; why it persists |
6,000-8,000 |
| 04 |
The other company hidden on X's balance sheet — {hidden asset} |
Investment portfolio / subsidiary / hidden value |
8,000-10,000 |
| 05 |
In the AI (or current narrative) era, is X a winner or loser |
Era variable: decompose the impact by business |
8,000-10,000 |
| 06 |
Reading X's financials the Buffett way |
Financial depth: gross margin / FCF / ROE / SBC |
8,000-10,000 |
| 07 |
{management quote} — is X's management worth entrusting |
Capital-allocation discipline + integrity test + succession |
8,000-10,000 |
| 08 |
At what price to buy, what signal to sell (finale) |
DCF 3-scenario + red lines + position framework |
10,000-12,000 |
Plus 00-series-overview.md as an index (unpublished).
3. Writing Style
Voice
- Direct, sharp, no filler — open with a number or a counterintuitive claim
- Value-investing frame — Buffett/Munger/Duan Yongping/Li Lu lenses woven in (no name-dropping)
- No preset stance — data first, logic next, conclusion last
- Show both sides — every core judgment carries a "but on the other hand..."
- Mobile preview — the first 18-20 characters must stand alone
Banned Words
| Banned |
Why |
Replace with |
| obviously / inevitably / certainly |
Subjective absolutism |
"the data shows" / "evidence suggests" |
| I think / I feel |
Subjective tone |
cut, or "under this framework" |
| textbook-level / brilliant |
Hype adjectives |
describe the concrete fact |
| severely mismatched / severely undervalued |
Strong subjective |
give the specific discount % |
| perfect / flawless |
One-sided |
add the counter-observation |
Title Style
- Hook with a contrast number or a counter-consensus claim ("15 years, 7 failed challenges"; "salary 42.92M = 0.0017% of profit")
- Neutral subtitle summarizing content
- Avoid hype metaphors: "the next Buffett", "the X of China", "GOAT" — all banned
4. Strict Fact-Check Checklist (the Core IP)
"Pseudo-precision" traps to watch for before writing
- Probability-weighted expected value:
30% × A + 50% × B + 20% × C = expected +X% is almost always garbage — the probabilities are pure subjective, giving readers false precision. List scenarios + triggers + direction only; do not compute a weighted expectation.
- Third-party MAU/share estimates: QuestMobile / 七麦 / CBNData differ hugely (2-3× at the same point). Use only the two most-credible as anchors; describe the rest qualitatively.
- Linear extrapolation of historical growth:
2025 +33% × 5y CAGR → 2030 X is financial illiteracy. Use scenario assumptions + high/low ranges; never a promise.
- Undisclosed shareholding: unlisted-company stakes are never publicly disclosed. Give a range, mark "unknowable".
- Strong attribution: "competitor failed because of X." List multiple causes; this article does no single attribution.
The 7 mandatory revision checks
□ 1. Cross-article number consistency: market cap, Non-IFRS net income, key holding % aligned across the series
□ 2. Caliber labeling: Non-IFRS / GAAP / Non-IFRS-SBC / FCF — which is used, clear throughout
□ 3. Double-counting scan: consolidated subs are NOT in the "investment portfolio"; SOTP doesn't count them twice
□ 4. Peer-comparison fairness: don't compare "core-business PE (cash + portfolio stripped)" with "peer PE (not stripped)"
□ 5. Probability-weighted expectations deleted (see above)
□ 6. Absolute language softened: grep "obviously|inevitably|severely|textbook|perfect"
□ 7. Third-party data sourced: every non-filing data point followed by "(source: X)"
Known hard-error risks (list before writing)
- Historical return multiples: use cumulative-invested basis (e.g. Riot 33×, not 58×)
- Shareholding %: use the latest filing/financial-app basis (e.g. Tencent's Meituan stake changes with disposals)
- "Distribution accounting": treated as disposal gain under IFRIC 17, recognized on declaration date
- Share count rebounds: SBC granted in clusters at year-start can lift share count short-term
5. Execution
Phase 1: Research (before writing 01-02)
get_financial_statements — last 5 years of annuals, latest quarterly
get_research_reports / web_search — at least 3 independent sell-side reports (find consensus + dissent)
- Optional:
run_swarm (e.g. equity_research_team or value_investing_committee) to generate an internal research draft
- Confirm the 8-part core theses with the user (avoid writing the wrong direction)
Phase 2: Writing (01→08 in order, no skipping)
- After each part,
write_file to reports/{company}/《Understanding {company}》/0X-XX.md
- Don't publish immediately — wait for user review
- Revise on feedback
Phase 3: Cross-Article Consistency Scan (after all 8)
This is the key differentiator. Use tools to scan:
read_file each part + report_audit (command=extract) to pull numbers (market cap, net income, holding %, PE) from each
- Cross-check the same number across parts — use
financial_rigor (command=cross_validate) to cross-validate the same metric's values across articles; flag >1% deviation as a caliber mismatch
read_file checks: is each term (FBS, SBC, Non-IFRS) defined at first use; do "see part 06" references actually resolve; do recaps match body numbers
- Absolute-language scan: grep "obviously|inevitably|severely|perfect" and soften each
Phase 4: Pre-publish Final Check
report_audit (command=verdict) as a gate on each part: extract numbers → verify → PASS/FAIL
- Confirm all numbers are traceable, no pseudo-precision, no absolutism
6. Revision-Feedback Handling
1. Verify facts first (don't just change)
If the user says "X is wrong", use get_financial_statements / web_search to cross-check the original; present "user's number vs what I found vs what I used".
2. Grade the revision
| Grade |
Type |
Handle |
| 🔥 Hard error |
wrong number / attribution / caliber |
Must fix |
| ⚠️ Subjective |
strong subjective word / hype metaphor |
Soften or cut |
| 🔬 Granularity |
source label, caliber refinement |
Balance against readability |
| ❓ Unreliable |
large third-party discrepancies |
Deleting is safer than editing |
3. Cascade check after a fix
Before fixing one spot, think "where else is this number/concept referenced":
- Market cap changed → cascade to PE / core-business PE / discount / FCF yield
- Holding % changed → fix TOP-10 sort + historical holding table + disposal list
- Caliber changed → fix first definition + later references + recap
7. What This Skill Does NOT Do
- Does not make investment decisions for the reader — every part ends with "not investment advice"
- Does not predict prices — only "scenarios + triggers"
- Does not compute a weighted "expected annualized return" — subjective probability misleads
- Does not write "famous investor X also holds" — using someone else's holding to back your judgment is anti-value-investing
- Does not force all 8 parts — if a part lacks enough standalone content (e.g. management isn't distinctive), merge it or reduce the count
One-liner: writing an "Understanding X" series is about revising strictly, not writing well — most finance long-form dies from pseudo-precise numbers, subjective weighted expectations, and absolute language. This skill exists to flag all those traps before writing and sweep them clean after (report_audit + financial_rigor.cross_validate).
1---2name: deep-company-series3description: Write a publication-grade 8-part deep-dive series on a single company (~120k words total): cognitive reset / moat / profit engine / hidden assets / era variable (e.g. AI) / financials Buffett-style / management / valuation+redlines. The core IP is NOT writing but REVISING — a strict fact-check checklist catches pseudo-precision (probability-weighted expectations, third-party MAU discrepancies, linear extrapolation), absolute language, and cross-article number inconsistencies that most finance long-forms violate. Each piece stands alone but shares one valuation/management/price framework. Use when the user wants textbook-level depth on one company for public publishing (a single research report or earnings note is NOT this — use investment-research / earnings-review instead).4---56# Deep-Company Series: An 8-Part Deep Dive on One Company78Write an 8-part deep-dive series (~120k words total) on a single company, from cognitive reset to a decision framework. **The core IP is not "writing well" but "revising strictly" — most finance long-form violates this skill's fact-check standard.**910## 1. When to Use1112The user wants "textbook-level" deep research on a company, published as a **series of long-form articles**. Distinct from a single research report:13- 8 parts, ~120k words, full loop from cognitive reset to a decision framework14- Each part stands alone (shareable singly) but shares one valuation / management / price framework15- Written for readers willing to spend 90 minutes understanding one company1617**Not for**: a single research report, earnings note, sector study — use other skills (fundamentals / earnings / sector).1819## 2. Series Template (8 Parts)2021| # | Title template | Core question | Words |22|---|----------------|---------------|-------|23| 01 | You think you understand X — you don't | Cognitive reset: break 3 common illusions | 4,000-5,000 |24| 02 | X's moat — `{one-line business essence}` | Is the moat deep; will it be there in 5/10 years | 6,000-8,000 |25| 03 | X's biggest profit engine — `{most profitable business}` | What is the core business; why it persists | 6,000-8,000 |26| 04 | The other company hidden on X's balance sheet — `{hidden asset}` | Investment portfolio / subsidiary / hidden value | 8,000-10,000 |27| 05 | In the AI (or current narrative) era, is X a winner or loser | Era variable: decompose the impact by business | 8,000-10,000 |28| 06 | Reading X's financials the Buffett way | Financial depth: gross margin / FCF / ROE / SBC | 8,000-10,000 |29| 07 | `{management quote}` — is X's management worth entrusting | Capital-allocation discipline + integrity test + succession | 8,000-10,000 |30| 08 | At what price to buy, what signal to sell (finale) | DCF 3-scenario + red lines + position framework | 10,000-12,000 |3132Plus `00-series-overview.md` as an index (unpublished).3334## 3. Writing Style3536### Voice37- **Direct, sharp, no filler** — open with a number or a counterintuitive claim38- **Value-investing frame** — Buffett/Munger/Duan Yongping/Li Lu lenses woven in (no name-dropping)39- **No preset stance** — data first, logic next, conclusion last40- **Show both sides** — every core judgment carries a "but on the other hand..."41- **Mobile preview** — the first 18-20 characters must stand alone4243### Banned Words4445| Banned | Why | Replace with |46|--------|-----|--------------|47| obviously / inevitably / certainly | Subjective absolutism | "the data shows" / "evidence suggests" |48| I think / I feel | Subjective tone | cut, or "under this framework" |49| textbook-level / brilliant | Hype adjectives | describe the concrete fact |50| severely mismatched / severely undervalued | Strong subjective | give the specific discount % |51| perfect / flawless | One-sided | add the counter-observation |5253### Title Style54- Hook with a **contrast number** or a **counter-consensus claim** ("15 years, 7 failed challenges"; "salary 42.92M = 0.0017% of profit")55- Neutral subtitle summarizing content56- **Avoid hype metaphors**: "the next Buffett", "the X of China", "GOAT" — all banned5758## 4. Strict Fact-Check Checklist (the Core IP)5960### "Pseudo-precision" traps to watch for before writing61621. **Probability-weighted expected value**: `30% × A + 50% × B + 20% × C = expected +X%` is almost always garbage — the probabilities are pure subjective, giving readers false precision. **List scenarios + triggers + direction only; do not compute a weighted expectation.**632. **Third-party MAU/share estimates**: QuestMobile / 七麦 / CBNData differ hugely (2-3× at the same point). **Use only the two most-credible as anchors; describe the rest qualitatively.**643. **Linear extrapolation of historical growth**: `2025 +33% × 5y CAGR → 2030 X` is financial illiteracy. **Use scenario assumptions + high/low ranges; never a promise.**654. **Undisclosed shareholding**: unlisted-company stakes are never publicly disclosed. **Give a range, mark "unknowable".**665. **Strong attribution**: "competitor failed because of X." List multiple causes; **this article does no single attribution.**6768### The 7 mandatory revision checks6970```71□ 1. Cross-article number consistency: market cap, Non-IFRS net income, key holding % aligned across the series72□ 2. Caliber labeling: Non-IFRS / GAAP / Non-IFRS-SBC / FCF — which is used, clear throughout73□ 3. Double-counting scan: consolidated subs are NOT in the "investment portfolio"; SOTP doesn't count them twice74□ 4. Peer-comparison fairness: don't compare "core-business PE (cash + portfolio stripped)" with "peer PE (not stripped)"75□ 5. Probability-weighted expectations deleted (see above)76□ 6. Absolute language softened: grep "obviously|inevitably|severely|textbook|perfect"77□ 7. Third-party data sourced: every non-filing data point followed by "(source: X)"78```7980### Known hard-error risks (list before writing)8182- Historical return multiples: use cumulative-invested basis (e.g. Riot 33×, not 58×)83- Shareholding %: use the latest filing/financial-app basis (e.g. Tencent's Meituan stake changes with disposals)84- "Distribution accounting": treated as disposal gain under IFRIC 17, recognized on declaration date85- Share count rebounds: SBC granted in clusters at year-start can lift share count short-term8687## 5. Execution8889### Phase 1: Research (before writing 01-02)90911. `get_financial_statements` — last 5 years of annuals, latest quarterly922. `get_research_reports` / `web_search` — at least 3 independent sell-side reports (find consensus + dissent)933. Optional: `run_swarm` (e.g. equity_research_team or value_investing_committee) to generate an internal research draft944. **Confirm the 8-part core theses with the user** (avoid writing the wrong direction)9596### Phase 2: Writing (01→08 in order, no skipping)9798- After each part, `write_file` to `reports/{company}/《Understanding {company}》/0X-XX.md`99- Don't publish immediately — wait for user review100- Revise on feedback101102### Phase 3: Cross-Article Consistency Scan (after all 8)103104This is the key differentiator. Use tools to scan:1051061. `read_file` each part + `report_audit` (`command=extract`) to pull numbers (market cap, net income, holding %, PE) from each1072. **Cross-check the same number across parts** — use `financial_rigor` (`command=cross_validate`) to cross-validate the same metric's values across articles; flag >1% deviation as a caliber mismatch1083. `read_file` checks: is each term (FBS, SBC, Non-IFRS) defined at first use; do "see part 06" references actually resolve; do recaps match body numbers1094. Absolute-language scan: grep "obviously|inevitably|severely|perfect" and soften each110111### Phase 4: Pre-publish Final Check112113- `report_audit` (`command=verdict`) as a gate on each part: extract numbers → verify → PASS/FAIL114- Confirm all numbers are traceable, no pseudo-precision, no absolutism115116## 6. Revision-Feedback Handling117118### 1. Verify facts first (don't just change)119If the user says "X is wrong", use `get_financial_statements` / `web_search` to cross-check the original; present "user's number vs what I found vs what I used".120121### 2. Grade the revision122123| Grade | Type | Handle |124|-------|------|--------|125| 🔥 Hard error | wrong number / attribution / caliber | Must fix |126| ⚠️ Subjective | strong subjective word / hype metaphor | Soften or cut |127| 🔬 Granularity | source label, caliber refinement | Balance against readability |128| ❓ Unreliable | large third-party discrepancies | **Deleting is safer than editing** |129130### 3. Cascade check after a fix131Before fixing one spot, think "where else is this number/concept referenced":132- Market cap changed → cascade to PE / core-business PE / discount / FCF yield133- Holding % changed → fix TOP-10 sort + historical holding table + disposal list134- Caliber changed → fix first definition + later references + recap135136## 7. What This Skill Does NOT Do137138- **Does not make investment decisions for the reader** — every part ends with "not investment advice"139- **Does not predict prices** — only "scenarios + triggers"140- **Does not compute a weighted "expected annualized return"** — subjective probability misleads141- **Does not write "famous investor X also holds"** — using someone else's holding to back your judgment is anti-value-investing142- **Does not force all 8 parts** — if a part lacks enough standalone content (e.g. management isn't distinctive), merge it or reduce the count143144---145146**One-liner**: writing an "Understanding X" series is about **revising strictly, not writing well** — most finance long-form dies from pseudo-precise numbers, subjective weighted expectations, and absolute language. This skill exists to flag all those traps before writing and sweep them clean after (`report_audit` + `financial_rigor.cross_validate`).