pumpfun-mechanics — скилл для Claude Code: математика PumpFun
Скилл для разбора механики PumpFun на Solana: формулы bonding curve, условия градации, парсинг событий и инструкций, миграция в PumpSwap.
npx skills add agiprolabs/claude-trading-skills --skill pumpfun-mechanics -a claude-codeЧто делает pumpfun-mechanics
Скилл даёт агенту готовые формулы и раскладки данных по PumpFun. Внутри — расчёт покупки и продажи токенов по виртуальной constant-product кривой, стоимость покупки точного количества токенов, капитализация и процент заполнения до градации. Все функции на Python, с округлением как в ончейн-программе.
Отдельный блок — градация: порог 85 SOL по реальным резервам, событие CompleteEvent, флаг complete в аккаунте bonding curve. Ещё есть таблицы program ID, PDA-сидов, дискриминаторов событий и раскладка аккаунта bonding curve по байтам. Для PumpSwap указано, что семантика инструкций перевёрнута: «buy» продаёт токены, «sell» покупает.
Скилл текстовый, без скриптов и зависимостей. Но формулы завязаны на точные значения lamports и raw-единиц: подставите человекочитаемые SOL и токены — получите мусор. Комиссия 1% в математику кривой не входит, её считают отдельно, поэтому круговой обмен теряет около 2% ещё до влияния на цену.
Какие задачи решает
- посчитать, сколько токенов придёт за заданное количество SOL
- узнать, сколько SOL нужно на покупку точного количества токенов
- определить процент заполнения bonding curve до градации
- распарсить TradeEvent из внутренних инструкций CPI
- разобрать раскладку аккаунта bonding curve по смещениям
Примеры запросов агенту
- посчитай, сколько токенов я получу за 2 SOL на этой bonding curve
- разбери TradeEvent из этой транзакции и покажи реальные резервы
- сколько процентов до градации осталось у этого минта
Как установить pumpfun-mechanics
1Через Skills CLI (Vercel)
npx skills add agiprolabs/claude-trading-skills --skill pumpfun-mechanics -a claude-code2Вручную: положить файлы
~/.claude/skills/pumpfun-mechanics/SKILL.mdПапка скилла целиком; для одного проекта — .claude/skills/pumpfun-mechanics/
1Через Skills CLI (Vercel)
npx skills add agiprolabs/claude-trading-skills --skill pumpfun-mechanics -a codex2Вручную: положить файлы
.agents/skills/pumpfun-mechanics/SKILL.mdДля всех проектов — ~/.agents/skills/
1Через Skills CLI (Vercel)
npx skills add agiprolabs/claude-trading-skills --skill pumpfun-mechanics -a cursor2Вручную: положить файлы
.cursor/skills/pumpfun-mechanics/SKILL.mdCursor читает и .agents/skills/, и .claude/skills/
1GitHub CLI
gh skill install agiprolabs/claude-trading-skills pumpfun-mechanics2Вручную: положить файлы
.github/skills/pumpfun-mechanics/SKILL.md1Через Skills CLI (Vercel)
npx skills add agiprolabs/claude-trading-skills --skill pumpfun-mechanics -a gemini-cli2Командой платформы
gemini skills install https://github.com/agiprolabs/claude-trading-skills --path skills/pumpfun-mechanicsВручную: положить файлы
.devin/skills/pumpfun-mechanics/SKILL.mdСтарый путь .windsurf/skills/ тоже читается
Через Skills CLI (Vercel)
npx skills add agiprolabs/claude-trading-skills --skill pumpfun-mechanics -a opencodeClaude.ai
Упакуйте папку в zip и загрузите в Settings → Capabilities → Skills
По шагам, с командами для каждой платформы: Как установить скилл в Claude Code: пять способов
Из того же набора48
Похожие
Рядом в теме «ИИ и ML»
Всё по теме «ИИ и ML» →Вопросы о pumpfun-mechanics
Как установить pumpfun-mechanics в Claude?
Выполните npx skills add agiprolabs/claude-trading-skills --skill pumpfun-mechanics -a claude-code. Скилл встанет в ~/.claude/skills/pumpfun-mechanics/SKILL.md.
Что делает pumpfun-mechanics?
Считает bonding curve PumpFun, определяет момент градации, парсит события и инструкции программы и описывает миграцию токена в PumpSwap.
Чем PumpSwap отличается от bonding curve после градации?
Это constant-product AMM с той же комиссией 1%, но базовый актив — WSOL, а инструкции перевёрнуты: «buy» продаёт токены, «sell» покупает.
Исходный текст
SKILL.md · MIT
---
name: pumpfun-mechanics
description: PumpFun bonding curve math, graduation mechanics, instruction parsing, and PumpSwap migration
---
# PumpFun Mechanics — Bonding Curves, Graduation & Instruction Parsing
PumpFun is the dominant Solana token launchpad. Understanding its bonding curve math, graduation process, and instruction formats is essential for analyzing new token launches, building trading strategies around graduation events, and parsing on-chain PumpFun activity.
## Bonding Curve Math
PumpFun uses a **virtual constant-product (CPMM)** bonding curve:
```
k = virtualSolReserves × virtualTokenReserves
```
### Initial Parameters
| Parameter | Value |
|-----------|-------|
| Initial Virtual SOL | 30 SOL (30,000,000,000 lamports) |
| Initial Virtual Tokens | ~1.073B tokens (1,073,000,000,000,000 raw, 6 decimals) |
| Token Total Supply | 1B tokens (1,000,000,000,000,000 raw) |
| Real Token Reserves | ~793M tokens (793,000,000,000,000 raw) |
| Real SOL Reserves | 0 (no real SOL at launch) |
| Fee | 1% (applied externally by the program) |
**Virtual vs Real**: Virtual reserves define the curve shape. Real reserves track actual withdrawable funds. The difference (1.073B - 793M = 280M virtual tokens) shapes the initial price but can never be withdrawn.
### Spot Price
```python
price_sol_per_token = virtual_sol_reserves / virtual_token_reserves
# In human-readable units:
price = (virtual_sol / 1e9) / (virtual_token / 1e6)
# At genesis: 30 / 1,073,000,000 ≈ 2.796e-8 SOL/token
# At graduation: ~4.1e-7 SOL/token (~14.7x from launch)
```
### Buy Tokens (SOL → Tokens)
```python
def buy_tokens(v_sol: int, v_tok: int, real_tok: int, sol_in: int) -> int:
"""Calculate tokens received for a given SOL input.
Args:
v_sol: Virtual SOL reserves (lamports).
v_tok: Virtual token reserves (raw).
real_tok: Real token reserves (raw).
sol_in: SOL to spend (lamports, BEFORE 1% fee).
Returns:
Tokens received (raw units).
"""
k = v_sol * v_tok
new_v_sol = v_sol + sol_in
new_v_tok = k // new_v_sol + 1 # +1 matches on-chain rounding
tokens_out = v_tok - new_v_tok
return min(tokens_out, real_tok)
```
### Sell Tokens (Tokens → SOL)
```python
def sell_tokens(v_sol: int, v_tok: int, real_sol: int, tokens_in: int) -> int:
"""Calculate SOL received for selling tokens.
Args:
v_sol: Virtual SOL reserves (lamports).
v_tok: Virtual token reserves (raw).
real_sol: Real SOL reserves (lamports).
tokens_in: Tokens to sell (raw units).
Returns:
SOL received (lamports, BEFORE 1% fee).
"""
k = v_sol * v_tok
new_v_tok = v_tok + tokens_in
new_v_sol = k // new_v_tok
sol_out = v_sol - new_v_sol - 1 # -1 matches on-chain floor rounding
return min(sol_out, real_sol)
```
### Buy Cost (Exact token amount → SOL needed)
```python
def buy_cost(v_sol: int, v_tok: int, tokens_wanted: int) -> int:
"""Calculate SOL needed to buy exact token amount.
Returns:
SOL cost in lamports (before fee). Returns max int if impossible.
"""
if tokens_wanted >= v_tok:
return 2**64 - 1 # impossible
k = v_sol * v_tok
new_v_tok = v_tok - tokens_wanted
new_v_sol = k // new_v_tok + 1
return new_v_sol - v_sol
```
### Fee Handling
The 1% fee is **not** part of the curve math. It's applied externally:
```python
# Buying: fee deducted from SOL input before curve
actual_sol_to_curve = sol_input * 0.99
# Selling: fee deducted from SOL output after curve
actual_sol_received = sol_from_curve * 0.99
# Roundtrip minimum cost: ~2% from fees alone, plus price impact
```
### Market Cap
```python
market_cap_sol = (token_total_supply * virtual_sol_reserves) / virtual_token_reserves
```
## Graduation
Graduation occurs when `realSolReserves` reaches **~85 SOL** (~$12K-14K depending on SOL price). Only ~1.4% of PumpFun tokens ever graduate.
### What Happens
1. `complete` flag set to `true` on bonding curve account
2. `CompleteEvent` emitted (discriminator `5f72619cd42e9808`)
3. Bonding curve stops accepting trades
4. ~$12K liquidity deposited to the destination DEX
5. Token becomes tradeable on PumpSwap (or Raydium for older tokens)
### Fill Percentage
```python
GRADUATION_THRESHOLD = 85_000_000_000 # 85 SOL in lamports
fill_pct = (real_sol_reserves / GRADUATION_THRESHOLD) * 100.0
```
### Migration Targets
- **March 2025+**: PumpSwap (`pAMMBay6oceH9fJKBRHGP5D4bD4sWpmSwMn52FMfXEA`) — native AMM, no migration fee
- **Before March 2025**: Raydium V4 (`675kPX9MHTjS2zt1qfr1NYHuzeLXfQM9H24wFSUt1Mp8`) — 6 SOL fee
### PumpSwap Post-Graduation
PumpSwap is a constant-product AMM with 1% fee (same as bonding curve). Key differences:
- Base asset is always WSOL, quote is token
- Instruction semantics are inverted: "buy" instruction sells tokens, "sell" instruction buys tokens
- Supports creator revenue sharing (0.05% of volume to original creator)
## Program IDs & Addresses
| Program/Account | Address |
|-----------------|---------|
| PumpFun Program | `6EF8rrecthR5Dkzon8Nwu78hRvfCKubJ14M5uBEwF6P` |
| PumpSwap Program | `pAMMBay6oceH9fJKBRHGP5D4bD4sWpmSwMn52FMfXEA` |
| Fee Program | `pfeeUxB6jkeY1Hxd7CsFCAjcbHA9rWtchMGdZ6VojVZ` |
| Global Account | `4wTV1YmiEkRvAtNtsSGPtUrqRYQMe5SKy2uB4Jjaxnjf` |
| Fee Recipient | `62qc2CNXwrYqQScmEdiZFFAnJR262PxWEuNQtxfafNgV` |
| Event Authority | `Ce6TQqeHC9p8KetsN6JsjHK7UTZk7nasjjnr7XxXp9F1` |
## Event Parsing
Events are Anchor-style: `sha256("event:<EventName>")[0..8]`
| Event | Discriminator (hex) |
|-------|-------------------|
| CreateEvent | `1b72a94ddeeb6376` |
| TradeEvent | `bddb7fd34ee661ee` |
| CompleteEvent | `5f72619cd42e9808` |
### TradeEvent Layout (after 8-byte discriminator)
```
mint: pubkey 32 bytes
solAmount: u64 8 bytes
tokenAmount: u64 8 bytes
isBuy: bool 1 byte
user: pubkey 32 bytes
timestamp: i64 8 bytes
virtualSolReserves: u64 8 bytes
virtualTokenReserves: u64 8 bytes
realSolReserves: u64 8 bytes
realTokenReserves: u64 8 bytes
```
**Critical**: Events are in CPI inner instructions. Search for discriminators **anywhere** in instruction data, not just at offset 0.
### Bonding Curve Account Layout
```
Offset 0: discriminator 8 bytes
Offset 8: virtualTokenReserves u64
Offset 16: virtualSolReserves u64
Offset 24: realTokenReserves u64
Offset 32: realSolReserves u64
Offset 40: tokenTotalSupply u64
Offset 48: complete bool (1 byte)
Offset 49: creator pubkey (32 bytes)
```
### PDA Derivation
| PDA | Seeds |
|-----|-------|
| Bonding Curve | `["bonding-curve", mint]` |
| Bonding Curve V2 | `["bonding-curve-v2", mint]` |
| Creator Vault | `["creator-vault", creator]` |
## Instruction Discriminators
| Instruction | Hex | Notes |
|-------------|-----|-------|
| buy_exact_sol_in (V2) | `38fc74089edfcd5f` | Current production buy |
| sell (V2) | `33e685a4017f83ad` | Current production sell |
| buy (V1/legacy) | `66063d1201daebea` | Legacy, still seen occasionally |
| create | `181ec828051c0777` | Token creation |
### Buy Instruction Data (24 bytes)
```
[0..8]: discriminator
[8..16]: spendable_sol_in u64 LE (total SOL budget, fees deducted internally)
[16..24]: min_tokens_out u64 LE (slippage floor)
```
### Sell Instruction Data (24 bytes)
```
[0..8]: discriminator
[8..16]: amount_tokens u64 LE (tokens to sell, raw)
[16..24]: min_sol_output u64 LE (minimum SOL out, lamports)
```
## Price Impact & Sizing
```python
def price_impact(v_sol: int, v_tok: int, sol_in: int) -> float:
"""Calculate price impact for a buy as a percentage."""
spot = v_sol / v_tok
tokens = buy_tokens(v_sol, v_tok, v_tok, sol_in)
if tokens == 0:
return float('inf')
exec_price = sol_in / tokens
return (exec_price / spot - 1) * 100
# Example: 1 SOL buy at genesis
# impact = price_impact(30_000_000_000, 1_073_000_000_000_000, 1_000_000_000)
# ≈ 3.3% price impact
```
## Files
### References
- `references/bonding_curve_math.md` — Complete mathematical derivations with worked examples
- `references/graduation_process.md` — Graduation threshold, migration, PumpSwap mechanics
- `references/instruction_reference.md` — Full instruction and event layouts for parsing
### Scripts
- `scripts/curve_calculator.py` — Interactive bonding curve calculator: price, impact, fill %
- `scripts/parse_events.py` — Parse PumpFun events from transaction data
© agiprolabs · MIT · agiprolabs/claude-trading-skills