Altcoin tracker API

Design an API that is stable, explicit, and auditable.

A static specification for portfolio, asset, market, scanner, analytics, AI, and alert endpoints with canonical identifiers, event time, quality flags, pagination, rate limits, and security controls.

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Static documentation preview

No live endpoint is implied

This page describes a data-model blueprint for an AltcoinTrack scanner and analytics API. The delivered static site does not operate a backend, issue API keys, or accept requests.

Core contracts

Predictability matters more than clever endpoint names

Stable identity

Use chain and contract or mint IDs, explicit venue and market types, and versioned mappings. Never rely on ticker symbols as primary keys.

Transparent time

Differentiate event, receipt, processing, and publication timestamps. State precision and correction policies.

Visible quality

Return freshness, mapping confidence, gaps, outliers, sample count, and source coverage.

Bounded resources

Limit time range, interval, assets, indicators, page size, and concurrent jobs. Explain cost units.

Deterministic pagination

Use stable sort keys and opaque cursors tied to snapshots or event boundaries.

Object-level security

Authorize every portfolio, wallet, alert, export, and sensitive field. Route-level login is not enough.

Conceptual resources

Organize endpoints around durable resources

  • Assets: canonical identity, metadata, representation, authorities, research status
  • Markets: venue, pair, type, quote, event time, spread, depth, quality
  • Portfolios: accounts, holdings, positions, liabilities, transactions, risk
  • Scanners: universe, filters, indicators, ranking, snapshot, evidence
  • Analytics: attribution, concentration, liquidity, scenarios, model version
  • Alerts: condition, state, history, evidence, acknowledgement, expiration
{
  "instrument_id": "solana:mint:...",
  "symbol": "TOKEN",
  "market": "venue:spot:TOKEN/USDC",
  "event_time": "2026-10-21T20:15:30.214Z",
  "published_time": "2026-10-21T20:15:30.391Z",
  "signal": {"type":"volume_expansion","window":"15m","version":"1.2"},
  "liquidity": {"spread_bps":18,"depth_usd_1pct":42000},
  "quality": ["verified_mapping"]
}

AI API use cases

  • Classify ambiguous transaction events with confidence and evidence
  • Summarize protocol, issuer, validator, or asset changes
  • Detect anomalies in balances, prices, mappings, or imports
  • Generate scenario explanations grounded in model outputs
  • Prioritize records that need human review

AI with guardrails

Return provenance, confidence, and model context

An AI endpoint should not overwrite observed facts silently. Identify inferred fields, model and policy version, uncertainty, evidence references, and whether a human accepted or changed the result.

For portfolio optimization, the request should include eligible assets, objective, constraints, liquidity assumptions, turnover policy, and scenarios. The response should provide alternatives and trade-offs instead of one unexplained best allocation.

Read the AI portfolio guide →

Developer checklist

Before an endpoint is production-ready

Specify

Schema, units, IDs, errors, timestamps, ordering, pagination, and compatibility.

Secure

Authentication, object and field authorization, key scope, rate limits, and audit logs.

Observe

Latency, freshness, gaps, provider drift, mapping errors, quota use, and adoption.

Retire

Inventory versions, publish deprecation dates, monitor usage, and remove old paths.

Turn the blueprint into an implementation plan.

Use the scanner API guide for identifier, chronology, indicator, liquidity, pagination, resource, and security decisions.

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