defi-bridge-route-planner
npx machina-cli add skill auralshin/agent-skills/defi-bridge-route-planner --openclawFiles (1)
SKILL.md
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DeFi Bridge Route Planner
Purpose
Compare cross-chain transfer options and produce a recommendation with explicit cost/time/risk tradeoffs and quote freshness guarantees.
Is adding a bridge aggregator helpful?
Yes. Aggregators are highly useful as the first discovery layer because they:
- reveal more route candidates (bridges + solvers) quickly,
- improve price competition,
- reduce manual route-by-route querying.
But aggregators should not be the only source. For high-value transfers, cross-check at least one direct bridge quote before final recommendation.
External dependency profile
- Dependency level: High for live route quality.
- Primary sources: bridge aggregators and solver quote APIs.
- Secondary sources: direct bridge quote endpoints.
- Validation/backfill: chain RPC gas estimates and route status pages.
- Offline fallback: cost-modeling only on user-supplied route snapshots.
Use this skill when
- The user wants to bridge assets across chains.
- The user asks for cheapest, fastest, safest, or balanced route.
- The user needs route comparison with fees, slippage, ETA, and risk.
Workflow
- Capture transfer intent (token, amount, source chain, destination chain, urgency, objective).
- Fetch route candidates from aggregators first. See
references/aggregator-integration.md. - Cross-check with direct bridge quotes for major candidates.
- Score routes with
scripts/route_cost_model.pyusing objective + risk limit. - Apply risk checks from
references/risk-checklist.md. - Return ranked options and recommended route, including quote freshness and caveats.
Data quality rules
- Treat expired quotes as ineligible.
- Reject routes above user risk tolerance.
- Always surface canonical vs wrapped destination token behavior.
- Show total cost decomposition (fees/slippage/gas).
Required output format
{
"intent": {
"from_chain": "string",
"to_chain": "string",
"token": "string",
"amount": 0,
"objective": "cheapest|fastest|safest|balanced"
},
"route_options": [
{
"route_name": "string",
"bridge_or_solver": "string",
"quote_source": "aggregator|direct_bridge",
"estimated_receive_amount": 0,
"total_cost_usd": 0,
"estimated_time_minutes": 0,
"risk_level": "low|medium|high",
"quote_age_seconds": 0,
"quote_valid": true,
"risk_notes": ["string"]
}
],
"recommended_route": {
"route_name": "string",
"reason": "string"
},
"critical_warnings": ["string"]
}
Bundled resources
references/aggregator-integration.mdreferences/risk-checklist.mdreferences/route-selection-policy.mdscripts/route_cost_model.pyassets/route-options-template.csv
Source
git clone https://github.com/auralshin/agent-skills/blob/main/skills/defi-bridge-route-planner/SKILL.mdView on GitHub Overview
DeFi Bridge Route Planner helps you evaluate cross-chain transfer options from aggregators and direct bridges. It produces explicit cost, ETA, and risk tradeoffs with quote freshness guarantees to inform a final recommendation.
How This Skill Works
Capture the transfer intent (token, amount, source/destination chains, urgency, objective). Then fetch route candidates from bridge aggregators and cross-check major candidates with direct bridge quotes. Finally score the routes using scripts/route_cost_model.py under your objective and risk limits, apply risk checks from risk checklist, and return ranked options with quote freshness and caveats.
When to Use It
- You want to bridge assets across chains and need a broad set of route options discovered quickly.
- You want Cheapest, Fastest, Safest, or Balanced route objectives and need a clear ranking.
- You require route comparison with fees, slippage, ETA, and risk for an informed decision.
- Quote freshness matters and you need explicit freshness guarantees for the selected route.
- You should validate top aggregator options with at least one direct-bridge quote before finalizing.
Quick Start
- Step 1: Capture transfer intent (token, amount, from_chain, to_chain, urgency, objective).
- Step 2: Fetch route candidates from aggregators, then cross-check major candidates with direct bridge quotes.
- Step 3: Review ranked options with quote freshness, apply risk checks, and select the recommended route.
Best Practices
- Start by querying bridge aggregators first to surface a wide set of route candidates quickly.
- Do not rely on aggregators alone; cross-check the top candidates with direct bridge quotes.
- Score routes with scripts/route_cost_model.py using objective and risk limits.
- Apply risk checks from references/risk-checklist.md to filter out high-risk options.
- Show total cost decomposition (fees, slippage, gas) and surface quote freshness and caveats.
Example Use Cases
- Example 1: Bridge 10,000 DAI from Ethereum to Polygon. Use aggregator quotes to identify multiple routes, then cross-check a top option with a direct bridge quote and choose the lowest total cost (fees+slippage+gas) while meeting the ETA target.
- Example 2: Fastest 5-minute transfer of ETH from Ethereum to Solana with low risk. Prioritize routes with the shortest estimated time and acceptable risk, verified against direct quotes.
- Example 3: Balanced 50,000 USDC from BSC to Avalanche for a medium-risk profile. Compare several routes, balancing cost, speed, and risk to select a reliable option.
- Example 4: High-value transfer requiring direct-quote validation. After aggregator discovery, obtain direct quotes for the top candidates to confirm pricing and freshness before finalizing.
- Example 5: Offline fallback scenario. If quotes expire or offline, rely on route_cost_model.py cost modeling using user-supplied route snapshots.
Frequently Asked Questions
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