Przejdź do treści
Biblioteka skilli
Marketing i treści · Research

study

/study

Wyciąga z postów wybranych autorów na LinkedIn i X powtarzalne kształty tekstów, np. otwarcia i zakończenia, bez ich zdań.

Repozytorium
open-stanley ↗
Licencja
MIT
Ostatnia zmiana repozytorium
26.10.2026

Ocena i bezpieczeństwo

100/ 100Klasa: dobry
Format25 / 25
Frontmatter z nazwą i opisem, poprawna nazwa, opis do 1024 znaków, nazwa zgodna z folderem.
Odkrywalność25 / 25
Opis mówi, kiedy użyć skilla, ma sensowną długość i jest w 3. osobie.
Treść35 / 35
Co najmniej 150 słów i do 500 linii, nagłówki, listy kroków, przykłady albo kod.
Higiena15 / 15
Bez zaślepek typu TODO, bez ścieżek Windows, z licencją.
Ryzykobrak sygnałów w skanie
Pliki w paczce
3
Skrypty
0
Komentarze HTML
0
Adresy URL w SKILL.md
0
Przestarzałość

Brak sygnałów. Repozytorium zmienione 26.10.2026, bez odwołań do wycofanych modeli i API.

Licencja

MIT, otwarta: można używać i zmieniać, z zachowaniem informacji o autorze.

Co robi i kiedy

Wyciąga z postów wybranych autorów na LinkedIn i X powtarzalne kształty tekstów, np. otwarcia i zakończenia, bez ich zdań.

Wyzwalacze z opisu

write like Paul Grahamlearn from Xwhy do their posts workstudy my competitor
Oryginalny opis (EN)

Learn how a specific writer wins on LinkedIn or X — Paul Graham, Dharmesh Shah, Yamini Rangan, Yuriy Zaremba, or anyone the user names — by reading their recent posts through the user's browser and extracting reusable *shapes* (openers, structures, endings, specificity moves, cadence) into a shapes catalog, never their sentences. Use when the user says "write like Paul Graham", "learn from X's posts", "why do their posts work", "study my competitor", or when write needs a shape for a lane. Ships with a catalog of the creators studied in September 2026.

Jak działa

  1. 1. Read
  2. 2. Extract shapes
  3. 3. Use
  4. 4. Ships with
Sekcje z nagłówków SKILL.md, w oryginale · 33 linii, 451 słów
Podgląd SKILL.md
---
name: study
description: Learn how a specific writer wins on LinkedIn or X — Paul Graham, Dharmesh Shah, Yamini Rangan, Yuriy Zaremba, or anyone the user names — by reading their recent posts through the user's browser and extracting reusable *shapes* (openers, structures, endings, specificity moves, cadence) into a shapes catalog, never their sentences. Use when the user says "write like Paul Graham", "learn from X's posts", "why do their posts work", "study my competitor", or when write needs a shape for a lane. Ships with a catalog of the creators studied in September 2026.
---

# Study: shapes, not sentences

"Copy Paul Graham's style" was the most repeated instruction in the chat log this plugin came from, and the paid product answered it with adjectives ("plain, one thought, no structure") and then wrote 120-word essays. A style is learned from examples and stored as *shapes*: the moves a writer makes that another writer can make with different material. Sentences stay with their author.

## 1. Read

Through the `browser` capability, logged in as the user: the creator's LinkedIn recent-activity page (posts tab) and X profile. Collect 20–40 posts with dates and engagement. Sort by engagement relative to their own median; the top quartile is what to learn from, the bottom quartile is what to avoid. Save the raw pull to `inbox/study-<handle>-<date>.md` (private; it's for analysis, never for reuse).

If the browser is unavailable, search results expose first lines and comment counts; that is enough for openers and cadence, not for structure. Say which you had.

## 2. Extract shapes

For each top-quartile post, name the moves. Use the vocabulary in `references/shape-vocabulary.md` so shapes are comparable across creators:

- **Opener**: event / claim / number / question-to-self / list-promise / "one of…"
- **Body**: single observation / story → lesson / argument-you-lost / numbered steps / contrast (then vs now) / product episode
- **Specificity**: what only they could know — exact number, named person, dated event, their own mistake
- **Ending**: flat last line / callback to opener / one open question / CTA with price / p.s.
- **Length band, paragraph shape, sentence-length spread**, punctuation habits (em dashes? parentheses? "p.s."?)
- **Cadence and mix**: posts/week, text vs image, how often they sell
- **What they never do** (from the bottom quartile and from absence): hashtags? questions? emoji?

Write `shapes/<handle>.md` in the vault: 5–10 shapes with a one-line description and *paraphrased* evidence ("opens on a lost argument: 'One of the debates I've had for 15+ years (and pretty much always lost)…'"; a quoted fragment under ~15 words is fine as a pointer, a whole post is not). Add the creator to `shapes/index.md`.

## 3. Use

`write` reads `shapes/` when the user asks for a shape ("PG-style comment", "a Dharmesh-style episode post") or when a lane in `strategy.md` names a reference creator. The shape supplies the moves; the user's story supplies every word of content; `voice.md` supplies the sentence-level voice. If a draft could be mistaken for the studied creator's post, it has failed: the reader should recognize the user.

## 4. Ships with

`references/creators-2026-09.md`: shapes for Paul Graham (X), Dharmesh Shah, Yamini Rangan, Yuriy Zaremba, and Vitalii Dodonov, derived from live reads of their feeds on 8 Sep 2026. Re-study every quarter; shapes drift with platforms.
Pliki w paczce (3)
  • SKILL.md 3 KB
  • references/creators-2026-09.md 5 KB
  • references/shape-vocabulary.md 2 KB

Wersje

RepozytoriumWynikLicencja
Ta strona · harmix/open-stanley100MIT
boston-harness-group/remote-factory100MIT
alaliqing/claude-paper100MIT
adamthewilliam/grepika100MIT
lucastamoios/skills95MIT
oskarijuurikkala/ac-hub-starter95CC-BY-4.0
DaniilKi/pali-canon-claude92MIT
flc1125/skills90MIT
TroyJLorents-GH/mega-motion90MIT

Migawka bazy z 13.11.2026 · wersja paczki 7ac1b2ae7e87 (skrót SHA-256 całej paczki)

Pobrania w ostatnich 30 dniach: 0 · ranking

Zgłoś problem z tym skillem: szkodliwa treść, błędny opis albo prośba autora o usunięcie.

Podobne skille

  • 100pg
    Pisze eseje, artykuły i wpisy blogowe głosem Paula Grahama, prostą mówioną prozą, która rozumuje na głos i unika sztucznego wypełniacza.
  • 90linkedin-writer
    Pisze posty na LinkedInie brzmiące jak konkretna osoba, budując profil głosu z własnych tekstów i redagując je samodzielnie.
  • 90paul-graham-perspective
    Doradza w sprawach startupów, pisania i produktu, myśląc tak jak Paul Graham, na podstawie jego esejów i wywiadów.
  • 100li-voice
    Mierzy głos użytkownika na LinkedIn z jego dawnych postów, zapisuje voice.md na dowodach i sprawdza każdy szkic pod kątem dryfu.
  • 100linkedin-writer
    Tworzy angażujące posty LinkedIn na podstawie sprawdzonych formatów, szablonów postów i dopasowania do głosu autora.
  • 90linkedin-content
    Pisze i publikuje posty na LinkedInie według danych z 2026 roku: hooki, treści uczące, formaty i 3 do 5 postów tygodniowo.

Uwagi i zgłoszenia

Wiadomość trafi do Bartosza Sokolińskiego. Adres e-mail jest potrzebny tylko do odpowiedzi. Szczegóły w polityce prywatności.