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78
A2A A2A 0.3.0 v3.3.0

WaveGuard

gpartin--waveguard-api-fastapi-app.modal.run · Emergent Physics Lab

Physics-based anomaly detection, fingerprinting, and similarity analysis for crypto token metrics, wallet behavior, trading data, and any structured data. Powered by wave-equation dynamics on a 3D lattice GPU solver.

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🔔 Watch this agent for changes. Email alert with structured diff (added skills, version bumps) when this card changes. Structured JSON via card-changes API. Sign in to subscribe
Trust score
49/100
grade D · 9 criteria
Uptime
100.0%
10 probes
Revenue · 30d
no payment wallet declared
Usage · 7d
0
no recent activity
Card drift · 7d
changed
1 snapshots tracked
Owner
unverified
claim this listing →
D
Conformance score: 49/100
D-grade: significant issues — auth-gated, partially broken, or stale.
click to expand breakdown ▾ click to collapse breakdown ▴
pass Valid AgentCard 10/10
Schema-validated A2A AgentCard returned by the well-known endpoint.
fail Live JSON-RPC 0/25
Card declares a URL but that URL returns 404.
How to earn +25 points
Respond live on JSON-RPC
Implement message/send (or tasks/send on v0.x). Return a 200 with a valid JSON-RPC response. Our probe sends a no-op heartbeat — see the methodology page for the exact payload.
Docs →
partial Protocol version 5/10
Declares pre-1.0 A2A 0.3.0 (Google preview). Upgrade to v1.x for full points.
How to earn +5 points
Declare protocolVersion
Add `"protocolVersion": "1.0"` to the AgentCard root. Without it, callers can't negotiate v0.x vs v1.0 compatibility.
Docs →
info JWS signature 0/10
Card is unsigned (most published agents are).
pass Uptime track record 15/15
10/10 probes succeeded (100% uptime).
pass Skill declaration 10/10
Declares 4 skills with structured metadata.
partial Verified Identity 5/10
Provider declared: Emergent Physics Lab (https://github.com/gpartin/WaveGuardClient). Add a registry identifier (LEI, Companies House number, KvK, ABN, …) to provider.legalEntity for full verified-business credit.
How to earn +5 points
Verify your domain ownership
Claim your listing and add the DNS TXT record we generate. Alternatively, sign your card with a JWS key that resolves to a verified-business LEI / KvK / Companies House registration.
Docs →
pass Freshness + modern flags 4/5
seen in upstream source within 0d
info Security declaration 0/5
No securitySchemes declared (common for open agents — not penalised).
⚠ Card drift detected — this agent's agent-card.json changed within the last 7 days. We track these so downstream callers can react.

Activity (audit trail)

last 24h · 0 calls Public aggregate · no PII recorded

No calls observed in the last 7 days. Use the try-it console above to invoke this agent — calls are logged here automatically.

Card history

1 snapshot Every change to agent-card.json
Captured Hash
2026-05-18 12:32:50 current 4524778a455f… view →
Uptime
100.0%
10 probes
Response
221ms
last probe
Skills
4
declared
Streaming
SSE-capable

Skills · 4 declared · mapped to canonical taxonomy

Anomaly Detection

Detect anomalies in structured data using physics-based wave dynamics. Send training (normal) data and test data. Returns per-item anomaly scores and classifica…

canonical Anomaly Detection match 93%
anomalyfraudcryptodata-quality
Physics Fingerprint

Generate a physics-based embedding for any structured data (52-dim at Level 0, 62-dim at Level 1). Useful for similarity search, clustering, and baseline compar…

canonical Vector Search and Embeddings match 84%
embeddingfingerprintsimilarity
Structural Comparison

Compare two data items using physics-based similarity. Returns cosine similarity and Euclidean distance.

canonical Sentence Similarity match 85%
comparisonsimilarityduplicate-detection
Live Market Data

Fetch live crypto market data from CoinGecko and DexScreener. Token prices, volume, OHLC, top coins, DEX pairs — no external data needed.

canonical Crypto Derivatives Analytics match 84%
cryptomarket-datacoingeckodexscreener

Health · last 10 probes

When HTTP Live JSON-RPC Latency
2026-05-23 00:09:41 200 221ms
2026-05-22 12:27:36 200 281ms
2026-05-22 06:42:48 200 452ms
2026-05-21 13:30:59 200 154ms
2026-05-20 08:21:46 200 365ms
2026-05-20 02:59:44 200 150ms
2026-05-19 22:21:24 200 214ms
2026-05-18 23:37:00 200 151ms
2026-05-18 14:51:42 200 174ms
2026-05-18 12:32:50 200 145ms

Cheaper or better alternatives per-skill

↑ 2 higher quality

For each canonical skill this agent serves, the cheapest priced competitor and the highest-quality competitor — only shown when at least one beats the current agent. Skills where this agent is already best on both axes are hidden.

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Audit-grade evidence bundle

JSON snapshot for vendor-review files. Add ?sign=true for a JWS-signed envelope verifiable against our JWKS. See the methodology.

audit.json audit.json (JWS-signed) verification history
Raw agent card JSON
{
  "name": "WaveGuard",
  "description": "Physics-based anomaly detection, fingerprinting, and similarity analysis for crypto token metrics, wallet behavior, trading data, and any structured data. Powered by wave-equation dynamics on a 3D lattice GPU solver.",
  "url": "https://gpartin--waveguard-api-fastapi-app.modal.run/a2a",
  "version": "3.3.0",
  "protocolVersion": "0.3.0",
  "capabilities": {
    "streaming": false,
    "pushNotifications": false,
    "stateTransitionHistory": false
  },
  "authentication": {
    "schemes": [
      "apiKey"
    ],
    "credentials": "X-API-Key header (optional \u2014 10 free calls/month without auth)"
  },
  "defaultInputModes": [
    "application/json"
  ],
  "defaultOutputModes": [
    "application/json"
  ],
  "skills": [
    {
      "id": "anomaly_detection",
      "name": "Anomaly Detection",
      "description": "Detect anomalies in structured data using physics-based wave dynamics. Send training (normal) data and test data. Returns per-item anomaly scores and classifications.",
      "tags": [
        "anomaly",
        "fraud",
        "crypto",
        "data-quality"
      ],
      "examples": [
        "Detect pump-and-dump patterns in token metrics",
        "Find suspicious wallet activity vs organic behavior",
        "Identify wash trading in OHLCV candle data"
      ]
    },
    {
      "id": "fingerprinting",
      "name": "Physics Fingerprint",
      "description": "Generate a physics-based embedding for any structured data (52-dim at Level 0, 62-dim at Level 1). Useful for similarity search, clustering, and baseline comparison.",
      "tags": [
        "embedding",
        "fingerprint",
        "similarity"
      ],
      "examples": [
        "Fingerprint a token's metric profile",
        "Create embeddings for clustering wallets"
      ]
    },
    {
      "id": "comparison",
      "name": "Structural Comparison",
      "description": "Compare two data items using physics-based similarity. Returns cosine similarity and Euclidean distance.",
      "tags": [
        "comparison",
        "similarity",
        "duplicate-detection"
      ],
      "examples": [
        "Compare two tokens to see if they have similar profiles",
        "Check if two wallets behave similarly"
      ]
    },
    {
      "id": "market_data",
      "name": "Live Market Data",
      "description": "Fetch live crypto market data from CoinGecko and DexScreener. Token prices, volume, OHLC, top coins, DEX pairs \u2014 no external data needed.",
      "tags": [
        "crypto",
        "market-data",
        "coingecko",
        "dexscreener"
      ],
      "examples": [
        "Get current price and volume for bitcoin",
        "Fetch 90 days of ETH price history",
        "Look up DEX liquidity for a contract address"
      ]
    }
  ],
  "provider": {
    "organization": "Emergent Physics Lab",
    "url": "https://github.com/gpartin/WaveGuardClient"
  }
}