
Opportunity Capture
pumpfun-mechanics
This Skill codifies PumpFun mechanics for precise on-chain analysis, strategy development, and instruction parsing. It implements the virtual constant-product (CPMM) bonding curve math used by PumpFun, including virtual vs real reserves, initial parameters (30 SOL virtual, ~1.
Overview
This Skill codifies PumpFun mechanics for precise on-chain analysis, strategy development, and instruction parsing.
This Skill codifies PumpFun mechanics for precise on-chain analysis, strategy development, and instruction parsing. It implements the virtual constant-product (CPMM) bonding curve math used by PumpFun, including virtual vs real reserves, initial parameters (30 SOL virtual, ~1.073B virtual tokens, ~793M real tokens), 1% program fee, and on-chain rounding behavior. Features include spot price computation, buy/sell token formulas, token output rounding (+1 matching on-chain), and expected graduation price behavior (~14.7x launch price). Use cases: build trading or graduation-arbitrage bots, backtest launch strategies, monitor and alert on PumpFun events, and parse program instructions and PumpSwap migration transactions. Core advantages are accurate, on-chain-faithful calculations, actionable signals for graduation events, and clear handling of fees and reserve bookkeeping for reliable analytics and tooling.
Skill.md
How this skill works
This Skill codifies PumpFun mechanics for precise on-chain analysis, strategy development, and instruction parsing. It implements the virtual constant-product (CPMM) bonding curve math used by PumpFun, including virtual vs real reserves, initial parameters (30 SOL virtual, ~1.
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
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)
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)
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)
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:
# 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
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
completeflag set totrueon bonding curve accountCompleteEventemitted (discriminator5f72619cd42e9808)- Bonding curve stops accepting trades
- ~$12K liquidity deposited to the destination DEX
- Token becomes tradeable on PumpSwap (or Raydium for older tokens)
Fill Percentage
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
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
Best used for
When to use it
This Skill codifies PumpFun mechanics for precise on-chain analysis, strategy development, and instruction parsing. It implements the virtual constant-product (CPMM) bonding curve math used by PumpFun, including virtual vs real reserves, initial parameters (30 SOL virtual, ~1.

01 · PRE-MEETING
Prepare a decision brief
Turn scattered evidence into a structured case before an investment committee meeting.

02 · TEAM WORKFLOW
Standardize handoffs
Create consistent research outputs across analysts, portfolio managers, and agents.

03 · LIVE UPDATE
Refresh the thesis
Update scenarios after a new catalyst, KPI release, or earnings result.
Community notes
Built to improve with use.
Feedback will appear here as this skill is used and reviewed.
Discover more
Related skills
View allThematic Investment Mapping
Map companies to a theme by revenue exposure, transmission channels, and second-order effects, then rank the best expressions of the theme. Use when building a thematic basket or researching idea…
capacitr
Capacitr provides single-call market discovery and paid analysis: paste a URL or free-text query and receive ranked Polymarket, Hyperliquid, and Deribit markets augmented with Quotient intelligence…
alphagbm-duan-analysis
AlphaGBM Duan Yongping Analysis packages Duan-style, seller-only option playbook into a single, trade-ready call. It produces three focused panels: Sell Put (compute strike, premium, delta, DTE,…