Alterscope Developer API

You operate a DAO treasury and want an agent that reallocates idle stablecoins toward the best risk-adjusted yield, subject to mandate constraints. Alterscope provides the data and the signals; the agent makes the call; your existing executor signs the transaction.

Alterscope does not execute transactions on your behalf. This recipe ends at the decision; the actual write to chain is your codebase.

What you build

A loop that, on each tick or on each vault.cap.changed event:

Pulls the candidate opportunity universe.
Scores each candidate against the current portfolio.
Picks the top reallocation that satisfies your mandate.
Emits a signed proposal to your executor.

1. Discover candidates

from alterscope import AlterscopeClient

client = AlterscopeClient(api_key="sk_live_...")

candidates = client.yield_opportunities.list(
    asset=["USDC", "USDT", "DAI"],
    chain=["ethereum", "base", "arbitrum"],
    risk_band=[1, 2],
    min_tvl_usd=10_000_000,
    sort_by="net_apy",
    order="desc",
    limit=25,
)

2. Score each candidate against the current book

current = load_treasury_positions()

best = None
best_delta = 0
for c in candidates.data:
    proposed = current + [{"opportunity_id": c.id, "notional_usd": 1_000_000}]
    analysis = client.portfolio.analyze(positions=proposed, include_scenarios=True)
    if analysis.risk.band > 2:
        continue
    delta = analysis.expected_apy_net - current_apy_net
    if delta > best_delta:
        best_delta = delta
        best = (c, analysis)

3. Apply mandate constraints

Encode your policy as code, not as prose. Common constraints:

Per-protocol cap: no more than 30% of treasury in a single protocol.
Oracle-provider cap: no more than 50% of treasury behind a single oracle provider.
Reject any candidate whose meta._agentic.freshness.status is not fresh.
Reject any candidate whose risk.dominant_factors[0] is oracle.stale_risk or peg.deviation.

def passes_mandate(candidate, analysis, current) -> bool:
    if analysis.meta._agentic.freshness.status != "fresh":
        return False
    if analysis.risk.dominant_factors[0].name in ("oracle.stale_risk", "peg.deviation"):
        return False
    return concentration_ok(current, candidate)

4. Emit a signed proposal

if best and passes_mandate(*best, current):
    candidate, analysis = best
    proposal = sign_proposal({
        "from": "treasury_idle_usdc",
        "to": candidate.id,
        "notional_usd": 1_000_000,
        "expected_apy_net": analysis.expected_apy_net,
        "rationale": analysis.risk.dominant_factors,
        "as_of_block": analysis.meta._agentic.freshness.as_of_block,
    })
    submit_to_executor(proposal)

5. Audit trail

Log every decision, including the ones that were rejected and why. The request_id in meta.request_id ties the proposal to the exact API responses that produced it.

6. Tier requirements

Factor attribution and stress scenarios require the Analyst tier or higher (the read:yield:detail scope). WebSocket triggers (a tighter feedback loop than polling) also require the Analyst tier or higher. Custom factors and per-route uplift require Enterprise.

​What you build

​1. Discover candidates

​2. Score each candidate against the current book

​3. Apply mandate constraints

​4. Emit a signed proposal

​5. Audit trail

​6. Tier requirements

What you build

1. Discover candidates

2. Score each candidate against the current book

3. Apply mandate constraints

4. Emit a signed proposal

5. Audit trail

6. Tier requirements