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Get Started Free →Comprehensive analysis of Uniswap Firepit burn economics: historical burn P&L, accumulation trends, fee source breakdown, competitive dynamics, and profitability projections. Governance-grade research report. Use when user asks "What's the burn economics?", "History of protocol fee burns", or "Average profit per burn."
.claude/skills/leoyeai-analyze-burn-economics/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 341% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 278% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 105% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 268% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 280% | 0% |
A pure research skill that produces a governance-grade analysis of the Uniswap protocol fee system's burn economics. This skill answers the questions that UNI holders, governance participants, and protocol researchers care about: How profitable have burns been? How are fees trending? What drives accumulation? When should parameters be adjusted?
No execution capability -- this is strictly analytical.
Why this is 10x better than calling tools individually:
get_burn_history call returns raw event logs. This skill cross-references each burn with the UNI price at that time (via get_token_price_history), the gas cost, and the assets claimed -- producing a per-burn profit/loss table that no single tool can generate.Activate when the user says anything like:
Do NOT use when the user wants to execute a burn (use seek-protocol-fees instead) or wants a real-time monitoring dashboard (use monitor-tokenjar instead).
| Parameter | Required | Default | How to Extract | | -------------------- | -------- | -------- | ------------------------------------------------------------------ | | chain | No | ethereum | Always Ethereum mainnet for TokenJar/Firepit | | days | No | 90 | Lookback period: "last 30 days", "past year" = 365 | | include-projections | No | true | "Just history" or "no projections" implies false |
ANALYZE-BURN-ECONOMICS PIPELINE
┌─────────────────────────────────────────────────────────────────────┐
│ │
│ Step 1: DATA COLLECTION (parallel MCP calls) │
│ ├── get_burn_history — all burns in lookback window │
│ ├── get_fee_accumulation_rate — current accumulation dynamics │
│ ├── get_firepit_state — current threshold and parameters │
│ ├── get_tokenjar_balances — current jar state │
│ ├── get_token_price (UNI) — current UNI price │
│ └── get_token_price_history (UNI) — UNI price over lookback │
│ │ │
│ ▼ (all data feeds into Step 2) │
│ │
│ Step 2: ANALYSIS (protocol-fee-seeker in analysis mode) │
│ ├── Per-burn P&L calculation │
│ ├── Burn frequency and timing analysis │
│ ├── Fee source and composition trends │
│ ├── Accumulation rate changes over time │
│ ├── Competitive dynamics (searcher behavior) │
│ └── Output: Historical Analysis Report │
│ │ │
│ ▼ (if include-projections: true) │
│ │
│ Step 3: PROJECTIONS │
│ ├── Next profitable burn timing │
│ ├── Expected profit at current rates │
│ ├── Sensitivity to UNI price changes │
│ ├── Impact of threshold parameter changes │
│ └── Output: Projection Report │
│ │
└─────────────────────────────────────────────────────────────────────┘Make all calls simultaneously for speed:
mcp__uniswap__get_burn_history with limit: 100 -- all burns in the lookback window.mcp__uniswap__get_fee_accumulation_rate -- current daily/weekly/monthly rates.mcp__uniswap__get_firepit_state -- current threshold, nonce, contract parameters.mcp__uniswap__get_tokenjar_balances -- current jar contents for context.mcp__uniswap__get_token_price for UNI -- current UNI price.mcp__uniswap__get_token_price_history for UNI with interval: "1d" and limit matching the lookback days -- UNI price history for cross-referencing burn events.Present to user:
textStep 1/3: Data Collection Complete Burn events found: 17 burns in last 90 days UNI price range: $5.80 - $8.20 (90d) Current UNI price: $7.00 Current jar value: $52,000 Accumulation rate: ~$7,400/day Analyzing burn economics...
Delegate to Task(subagent_type:protocol-fee-seeker) in analysis mode with all collected data:
Produce a comprehensive burn economics analysis report.
Historical data:
- Burn history: {full burn event data from Step 1}
- UNI price history: {daily OHLCV from Step 1}
- Current accumulation rates: {from Step 1}
- Current Firepit state: threshold={threshold}, nonce={nonce}
- Current TokenJar balances: {from Step 1}
- Current UNI price: ${price}
- Lookback period: {days} days
Analysis tasks:
1. For each burn event, calculate:
- UNI cost at the time of burn (threshold * UNI price at that block)
- Gas cost (from transaction receipt)
- Gross value of assets claimed
- Net profit/loss
- ROI percentage
2. Compute aggregate statistics:
- Total burns in period
- Average profit per burn
- Median profit per burn
- Best and worst burns
- Total value distributed through burns
- Average time between burns
3. Analyze trends:
- Is burn profitability increasing or decreasing?
- Is burn frequency increasing (more competition)?
- How has fee composition changed? (more WETH vs USDC vs others)
- Correlation between UNI price and burn profitability
4. Competitive dynamics:
- How many unique searcher addresses?
- Are the same addresses burning repeatedly?
- What profitability level triggers burns? (min ROI observed)
Return a structured analysis report with all metrics.Present to user after completion:
textStep 2/3: Historical Analysis Complete 17 burns analyzed over 90 days. Total value distributed: $612,000 Average profit: $18,400/burn (65.7% avg ROI) Generating projections...
The agent produces forward-looking projections based on the analysis:
Based on the historical analysis, produce projections:
Current state:
- TokenJar value: ${jar_value}
- Accumulation rate: ${daily_rate}/day
- UNI price: ${uni_price}
- Burn threshold: {threshold} UNI
- Burn cost: ${burn_cost}
Projections to compute:
1. Time to next profitable burn (if not already profitable).
2. Expected profit at current accumulation rate (1-day, 3-day, 7-day projections).
3. Sensitivity analysis: how does profitability change if UNI price moves +/-20%?
4. Threshold sensitivity: what if threshold changed to 2,000 or 8,000 UNI?
5. Break-even analysis: at what UNI price does the current jar become unprofitable?textBurn Economics Report (Last 90 Days) ══════════════════════════════════════ SUMMARY STATISTICS ══════════════════════════════════════ Total Burns: 17 Total Value Claimed: $612,000 Total UNI Burned: 68,000 UNI ($476,000) Total Gas Spent: $765 Total Net Profit: $135,235 Average Profit/Burn: $7,955 Median Profit/Burn: $6,200 Average ROI: 65.7% Average Burn Interval: 5.3 days ══════════════════════════════════════ BURN HISTORY ══════════════════════════════════════ Date Jar Value UNI Cost Gas Net Profit ROI Searcher 2026-02-03 $52,000 $28,000 $45 $23,955 85.4% 0xab..12 2026-01-28 $41,200 $27,200 $38 $13,962 51.3% 0xcd..34 2026-01-22 $38,500 $26,800 $42 $11,658 43.5% 0xab..12 2026-01-17 $35,100 $25,600 $35 $9,465 37.0% 0xef..56 ... ... ... ... ... ... ... (17 burns total) Best Burn: 2026-02-03 — $23,955 profit (85.4% ROI) Worst Burn: 2025-12-15 — $1,200 profit (4.3% ROI) ══════════════════════════════════════ FEE COMPOSITION ══════════════════════════════════════ Token Avg Share Trend (90d) WETH 35.2% Stable USDC 27.8% Growing (+3.2%) USDT 16.5% Stable WBTC 11.4% Declining (-1.8%) DAI 6.1% Declining (-0.5%) Other 3.0% Growing (+1.1%) ══════════════════════════════════════ ACCUMULATION TRENDS ══════════════════════════════════════ Current Rate: $7,400/day 30d Avg Rate: $6,800/day 90d Avg Rate: $6,200/day Trend: INCREASING (+19.4% over 90 days) Rate by Source (estimated): V3 Fees: ~$4,200/day (56.8%) V4 Fees: ~$1,400/day (18.9%) UniswapX: ~$1,100/day (14.9%) V2 Fees: ~$500/day (6.8%) Unichain: ~$200/day (2.7%) ══════════════════════════════════════ COMPETITIVE DYNAMICS ══════════════════════════════════════ Unique Searchers: 4 addresses (last 90d) Most Active: 0xab..12 (8 of 17 burns, 47%) Min ROI at Burn: 4.3% (some searchers burn at thin margins) Avg ROI at Burn: 65.7% Competition Trend: Increasing (2 new searchers in last 30d) ══════════════════════════════════════ PROJECTIONS ══════════════════════════════════════ Current Jar: $52,000 (PROFITABLE — $23,955 net) Next 10% ROI: Already exceeded Next 100% ROI: ~0.5 days If jar were empty today: Break-even: ~3.8 days ($28,045 / $7,400/day) 10% ROI: ~4.2 days 50% ROI: ~5.7 days UNI Price Sensitivity (current jar $52,000): UNI at $5.60 (-20%): Burn cost $22,445 → Profit $29,555 (131.7% ROI) UNI at $7.00 (now): Burn cost $28,045 → Profit $23,955 (85.4% ROI) UNI at $8.40 (+20%): Burn cost $33,645 → Profit $18,355 (54.6% ROI) UNI at $13.00 (break-even): Burn cost $52,045 → Profit -$45 Threshold Sensitivity (current UNI price $7.00): 2,000 UNI: Burn cost $14,045 → Profit $37,955 (270.2% ROI) 4,000 UNI: Burn cost $28,045 → Profit $23,955 (85.4% ROI) ← current 8,000 UNI: Burn cost $56,045 → Profit -$4,045 (NOT PROFITABLE) ══════════════════════════════════════ GOVERNANCE IMPLICATIONS ══════════════════════════════════════ - The fee system is healthy: accumulation rate is growing (+19.4% over 90d), driven primarily by V3 and emerging V4 volume. - Current threshold (4,000 UNI) produces healthy competition with 4 active searchers and average 5.3-day burn intervals. - Increasing the threshold to 8,000 UNI would make burns unprofitable at current rates unless the jar accumulates for ~7.6 days. - V4 fee contribution is growing (18.9%) and may overtake V2 within 30 days at current trajectory.
textBurn Economics Summary (Last {days} Days) Burns: {count} | Total Distributed: ${total} Avg Profit: ${avg_profit}/burn ({avg_roi}% ROI) Avg Interval: {days} days Accumulation: ${daily_rate}/day (trend: {direction}) Current Jar: ${jar_value} ({PROFITABLE | NOT_PROFITABLE})
| Error | User-Facing Message | Suggested Action | | ---------------------------- | ------------------------------------------------------------------------- | ----------------------------------------- | | No burn history | "No burns found in the last {days} days." | Increase lookback period | | Insufficient burns | "Only {count} burns found. Analysis may be limited." | Increase lookback or accept limited data | | UNI price history unavailable| "Could not retrieve UNI price history. Per-burn P&L will be approximate." | Proceed with current price as fallback | | Accumulation data sparse | "Limited accumulation data. Rate estimates may be imprecise." | Try a larger lookback window | | Token price unavailable | "Could not price {token}. Some jar values may be incomplete." | Token may be exotic or illiquid | | RPC connection failed | "Cannot connect to Ethereum RPC. Analysis unavailable." | Check RPC configuration | | Lookback too large | "Lookback of {days} days exceeds available data." | Reduce lookback period |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 36,120 | 5,446 | -85% | 1 | 1 | 0% | 6,212 | 4,490 | -28% | 0 | 0 | — |
case-02 | pass→fail | 12,266 | 4,857 | -60% | 1 | 1 | 0% | 1,821 | 4,458 | +145% | 0 | 0 | — |
case-03 | fail→fail | 58,900 | 5,049 | -91% | 1 | 1 | 0% | 4,679 | 4,164 | -11% | 0 | 0 | — |
case-04 | fail→pass | 6,170 | 4,934 | -20% | 1 | 1 | 0% | 1,120 | 4,934 | +341% | 0 | 0 | — |
case-05 | fail→fail | 25,163 | 8,588 | -66% | 1 | 1 | 0% | 6,163 | 4,859 | -21% | 0 | 0 | — |
case-06 | fail→fail | 13,518 | 11,184 | -17% | 1 | 1 | 0% | 2,592 | 4,150 | +60% | 0 | 0 | — |
case-07 | fail→pass | 19,083 | 2,172 | -89% | 1 | 1 | 0% | 1,167 | 4,410 | +278% | 0 | 0 | — |
case-08 | pass→pass | 14,571 | 3,437 | -76% | 1 | 1 | 0% | 2,673 | 4,730 | +77% | 0 | 0 | — |
case-09 | pass→fail | 8,414 | 5,549 | -34% | 1 | 1 | 0% | 1,470 | 4,595 | +213% | 0 | 0 | — |
case-14 | fail→pass | 13,278 | 2,525 | -81% | 1 | 1 | 0% | 2,214 | 4,545 | +105% | 0 | 0 | — |
case-10 | fail→pass | 6,837 | 1,485 | -78% | 1 | 1 | 0% | 1,161 | 4,268 | +268% | 0 | 0 | — |
case-11 | fail→pass | 6,724 | 1,695 | -75% | 1 | 1 | 0% | 1,137 | 4,315 | +280% | 0 | 0 | — |
case-12 | fail→pass | 15,582 | 5,501 | -65% | 1 | 1 | 0% | 2,777 | 5,074 | +83% | 0 | 0 | — |
case-13 | fail→pass | 2,922 | 2,298 | -21% | 1 | 1 | 0% | 411 | 4,511 | +998% | 0 | 0 | — |
case-15 | fail→fail | 8,182 | 2,606 | -68% | 1 | 1 | 0% | 1,414 | 4,543 | +221% | 0 | 0 | — |
case-16 | fail→fail | 13,761 | 6,339 | -54% | 1 | 1 | 0% | 1,958 | 4,942 | +152% | 0 | 0 | — |
case-17 | pass→pass | 25,438 | 1,977 | -92% | 1 | 1 | 0% | 1,692 | 4,289 | +153% | 0 | 0 | — |
case-18 | fail→pass | 10,314 | 2,142 | -79% | 1 | 1 | 0% | 1,835 | 4,358 | +137% | 0 | 0 | — |
case-19 | fail→pass | 3,605 | 2,533 | -30% | 1 | 1 | 0% | 447 | 4,467 | +899% | 0 | 0 | — |
case-20 | pass→pass | 15,356 | 3,467 | -77% | 1 | 1 | 0% | 2,104 | 4,588 | +118% | 0 | 0 | — |
case-21 | pass→pass | 2,618 | 1,770 | -32% | 1 | 1 | 0% | 413 | 4,271 | +934% | 0 | 0 | — |
case-22 | fail→pass | 2,622 | 3,334 | +27% | 1 | 1 | 0% | 308 | 4,656 | +1412% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 16 counted toward the lift figure. The other 6 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +36 percentage points is the difference between those two pass rates over the 16 comparable cases. 2 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.