QuantJourney Research Agent Fabric
agents.quantjourney.cloud
· QuantJourney
Agent gateway for bounded, evidence-backed investment research. Four deterministic MCP-backed queries may be enabled independently of generic A2A execution. Machine OAuth, x402 v2 and fallback prepaid accounting are available.
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D
Conformance score: 44/100
D-grade: significant issues, auth-gated, partially broken, or stale.
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agent-card.json changed within the last 7 days. We track these so downstream callers can react.
Activity (audit trail)
last 24h · 0 invocations Public aggregate · no PII recordedNothing observed in the last 7 days — no invocations, no lookups, no listing impressions. Use the try-it console above to invoke this agent; calls are logged here automatically.
Card history
1 snapshot Every change toagent-card.json
| Captured | Hash | |
|---|---|---|
| 2026-08-29 10:47:43 current | 1cff6a80e38b… |
view → |
Endpoints
| Agent card | https://agents.quantjourney.cloud/.well-known/agent-card.json |
| Provider | https://quantjourney.cloud |
| Docs | https://agents.quantjourney.cloud/llms-full.txt |
Skills · 15 declared · mapped to canonical taxonomy
Return a free, bounded factual ticker snapshot with price, selected metrics, freshness and explicit coverage gaps.
Prepare an evidence-backed earnings preview with consensus, revisions, dispersion, historical surprises, valuation context and explicit review questions.
Reconcile the latest reported earnings with consensus, estimate changes, adjusted-close reactions, SPY-adjusted CAR and explicit thesis-review questions.
Combine congressional disclosures and government-contract evidence with disclosure-lag warnings.
Build a full company research note grounded in QJ fundamentals, metrics, estimates, price history and lineage.
Create a bounded valuation analysis using QJ metrics, fundamentals, estimates and explicit scenario assumptions.
Audit or update a living thesis against new evidence, catalysts, invalidation conditions and review triggers.
Review portfolio exposures, event risk, concentration and material evidence changes without taking execution actions.
Analyze 13F, ownership and institutional positioning with filing-period and publication-lag controls.
Create a dated macro regime brief using rates, commodities, benchmarks and scheduled macro events.
Build a dated watchlist of earnings, dividends, macro, split and thesis-review catalysts with coverage status.
Generate research candidates from screens, ranks, government and congressional evidence without presenting them as recommendations.
Challenge an existing analysis for unsupported claims, confirmation bias, data gaps and portfolio risk.
Prepare a non-executing rebalance proposal from drift, concentration, risk and benchmark evidence.
Map thematic supply chains, chokepoints, beneficiaries and exposed baskets using profiles, contracts and metrics.
Health · last 2 probes
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Markdown / HTML snippets
[](https://agenstry.com/agents/agents.quantjourney.cloud) [](https://agenstry.com/agents/agents.quantjourney.cloud) [](https://agenstry.com/agents/agents.quantjourney.cloud) [](https://agenstry.com/agents/agents.quantjourney.cloud)
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.
Raw agent card JSON
{
"name": "QuantJourney Research Agent Fabric",
"description": "Agent gateway for bounded, evidence-backed investment research. Four deterministic MCP-backed queries may be enabled independently of generic A2A execution. Machine OAuth, x402 v2 and fallback prepaid accounting are available.",
"supportedInterfaces": [
{
"url": "https://agents.quantjourney.cloud",
"protocolBinding": "HTTP+JSON",
"protocolVersion": "1.0"
}
],
"provider": {
"organization": "QuantJourney",
"url": "https://quantjourney.cloud"
},
"version": "0.14.2",
"documentationUrl": "https://agents.quantjourney.cloud/llms-full.txt",
"capabilities": {
"streaming": false,
"pushNotifications": false,
"extendedAgentCard": false,
"boundedQueryExecution": true,
"extensions": [
{
"uri": "https://agents.quantjourney.cloud/extensions/evidence/v1",
"description": "QJ evidence, freshness, product-grade and lineage contract.",
"required": true
},
{
"uri": "https://agents.quantjourney.cloud/v1/x402",
"description": "QJ x402 v2 price, network, settlement and route contract.",
"required": false
}
]
},
"securitySchemes": {
"qj_agent_oauth": {
"oauth2SecurityScheme": {
"flows": {
"clientCredentials": {
"tokenUrl": "https://agents.quantjourney.cloud/oauth/token",
"scopes": {
"agents:discover": "Read public and caller-specific agent discovery metadata.",
"agents:billing": "Read the client wallet and create bounded top-up sessions.",
"agents:query": "Submit bounded agent queries when execution is enabled."
}
}
}
}
}
},
"securityRequirements": [
{
"schemes": {
"qj_agent_oauth": {
"list": [
"agents:query"
]
}
}
}
],
"defaultInputModes": [
"text/plain",
"application/json"
],
"defaultOutputModes": [
"application/json",
"text/markdown"
],
"skills": [
{
"id": "qj-company-snapshot-lite",
"name": "Company Snapshot Lite",
"description": "Return a free, bounded factual ticker snapshot with price, selected metrics, freshness and explicit coverage gaps.",
"tags": [
"equity",
"snapshot",
"price",
"metrics"
],
"examples": [
"Return the free company snapshot for NVDA."
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "qj-earnings-preview",
"name": "Earnings Preview",
"description": "Prepare an evidence-backed earnings preview with consensus, revisions, dispersion, historical surprises, valuation context and explicit review questions.",
"tags": [
"earnings",
"estimates",
"revisions",
"valuation"
],
"examples": [
"Prepare the free earnings preview for NVDA."
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "qj-earnings-recap",
"name": "Earnings Recap",
"description": "Reconcile the latest reported earnings with consensus, estimate changes, adjusted-close reactions, SPY-adjusted CAR and explicit thesis-review questions.",
"tags": [
"earnings",
"recap",
"surprise",
"event-study"
],
"examples": [
"Prepare the free earnings recap for NVDA."
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "qj-congress-gov-signals",
"name": "Congress and Government Signals",
"description": "Combine congressional disclosures and government-contract evidence with disclosure-lag warnings.",
"tags": [
"congress",
"government",
"contracts",
"policy"
],
"examples": [
"Find recent congressional and government-contract signals relevant to PLTR."
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "qj-equity-deep-dive",
"name": "Equity Deep Dive",
"description": "Build a full company research note grounded in QJ fundamentals, metrics, estimates, price history and lineage.",
"tags": [
"equity",
"fundamentals",
"valuation",
"research"
],
"examples": [
"Produce an evidence-backed deep dive on NVDA as of 2026-08-21."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
},
{
"id": "qj-valuation-workbench",
"name": "Valuation Workbench",
"description": "Create a bounded valuation analysis using QJ metrics, fundamentals, estimates and explicit scenario assumptions.",
"tags": [
"valuation",
"dcf",
"comps",
"scenarios"
],
"examples": [
"Compare NVDA valuation to peers under bear, base and bull assumptions."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
},
{
"id": "qj-thesis-tracker",
"name": "Living Thesis Tracker",
"description": "Audit or update a living thesis against new evidence, catalysts, invalidation conditions and review triggers.",
"tags": [
"thesis",
"monitoring",
"evidence",
"decisions"
],
"examples": [
"Audit the current TSM thesis and report only evidence that changed since the prior review."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
},
{
"id": "qj-portfolio-monitor",
"name": "Portfolio Monitor",
"description": "Review portfolio exposures, event risk, concentration and material evidence changes without taking execution actions.",
"tags": [
"portfolio",
"risk",
"events",
"monitoring"
],
"examples": [
"Identify today's material portfolio risks and cite the supporting QJ evidence."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
},
{
"id": "qj-institutional-flow",
"name": "Institutional Flow",
"description": "Analyze 13F, ownership and institutional positioning with filing-period and publication-lag controls.",
"tags": [
"13f",
"ownership",
"institutional",
"flow"
],
"examples": [
"Summarize institutional positioning changes in NBIS and their reporting lag."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
},
{
"id": "qj-macro-regime-brief",
"name": "Macro Regime Brief",
"description": "Create a dated macro regime brief using rates, commodities, benchmarks and scheduled macro events.",
"tags": [
"macro",
"regime",
"rates",
"commodities"
],
"examples": [
"Describe the current US macro regime and its most important review triggers."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
},
{
"id": "qj-catalyst-calendar",
"name": "Catalyst Calendar",
"description": "Build a dated watchlist of earnings, dividends, macro, split and thesis-review catalysts with coverage status.",
"tags": [
"catalysts",
"calendar",
"events",
"watchlist"
],
"examples": [
"Build the next 30-day catalyst calendar for NVDA, ORCL and TSM."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
},
{
"id": "qj-idea-generation",
"name": "Idea Generation",
"description": "Generate research candidates from screens, ranks, government and congressional evidence without presenting them as recommendations.",
"tags": [
"ideas",
"screening",
"ranking",
"research"
],
"examples": [
"Find five US equities with improving quality and a dated external catalyst."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
},
{
"id": "qj-risk-bias-review",
"name": "Risk and Bias Review",
"description": "Challenge an existing analysis for unsupported claims, confirmation bias, data gaps and portfolio risk.",
"tags": [
"risk",
"bias",
"bear-case",
"quality"
],
"examples": [
"Challenge this NVDA thesis and distinguish contradictory evidence from missing data."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
},
{
"id": "qj-portfolio-rebalance-planner",
"name": "Portfolio Rebalance Planner",
"description": "Prepare a non-executing rebalance proposal from drift, concentration, risk and benchmark evidence.",
"tags": [
"portfolio",
"rebalance",
"risk",
"benchmark"
],
"examples": [
"Prepare a rebalance proposal that reduces factor concentration without placing orders."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
},
{
"id": "qj-supply-chain-theme-research",
"name": "Supply Chain Theme Research",
"description": "Map thematic supply chains, chokepoints, beneficiaries and exposed baskets using profiles, contracts and metrics.",
"tags": [
"supply-chain",
"themes",
"chokepoints",
"baskets"
],
"examples": [
"Map the AI power-infrastructure supply chain and identify evidence-backed bottlenecks."
],
"inputModes": [
"text/plain",
"application/json"
],
"outputModes": [
"application/json",
"text/markdown"
]
}
]
}