Xpersona Agent
Crawled www.anthropic.com ebb73093
PyTorch, JAX, and Triton. Model architecture and Training Methodology Claude Haiku 4.5 was pretrained on a proprietary mix of large, diverse datasets to acquire language capabilities. After the pretraining process, th... PyTorch, JAX, and Triton. Model architecture and Training Methodology Claude Haiku 4.5 was pretrained on a proprietary mix of large, diverse datasets to acquire language capabilities. After the pretraining process, the model underwent substantial post-training and fine-tuning, the object of which is to make it a helpful, honest, and harmless assistant. This involves a variety of techniques, including reinforcement le
Overall rank
#77
Adoption
No public adoption signal
Trust
Unknown
Freshness
Mar 14, 2026
Freshness
Last checked Mar 14, 2026
Best For
Crawled www.anthropic.com ebb73093 is best for general automation workflows where documented compatibility matters.
Not Ideal For
Contract metadata is missing or unavailable for deterministic execution.
Evidence Sources Checked
editorial-content, GITHUB REPOS, runtime-metrics, public facts pack
Overview
Key links, install path, reliability highlights, and the shortest practical read before diving into the crawl record.
Verifiededitorial-content
Overview
Key links, install path, reliability highlights, and the shortest practical read before diving into the crawl record.
Overview
Executive Summary
PyTorch, JAX, and Triton. Model architecture and Training Methodology Claude Haiku 4.5 was pretrained on a proprietary mix of large, diverse datasets to acquire language capabilities. After the pretraining process, th... PyTorch, JAX, and Triton. Model architecture and Training Methodology Claude Haiku 4.5 was pretrained on a proprietary mix of large, diverse datasets to acquire language capabilities. After the pretraining process, the model underwent substantial post-training and fine-tuning, the object of which is to make it a helpful, honest, and harmless assistant. This involves a variety of techniques, including reinforcement le Capability contract not published. No trust telemetry is available yet. Last updated 4/14/2026.
Trust score
Unknown
Compatibility
Profile only
Freshness
Mar 14, 2026
Vendor
Anthropic
Artifacts
0
Benchmarks
0
Last release
Unpublished
Install & run
Setup Snapshot
- 1
Setup complexity is MEDIUM. Standard integration tests and API key provisioning are required before connecting this to production workloads.
- 2
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.
Evidence & Timeline
Public facts grouped by evidence type, plus release and crawl events with provenance and freshness.
Verifiededitorial-content
Evidence & Timeline
Public facts grouped by evidence type, plus release and crawl events with provenance and freshness.
Public facts
Evidence Ledger
Vendor (1)
Vendor
Anthropic
Security (1)
Handshake status
UNKNOWN
Integration (1)
Crawlable docs
6 indexed pages on the official domain
Artifacts & Docs
Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.
Self-declaredGITHUB REPOS
Artifacts & Docs
Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.
Captured outputs
Artifacts Archive
Extracted files
0
Examples
0
Snippets
0
Languages
Unknown
Editorial read
Docs & README
Docs source
GITHUB REPOS
Editorial quality
ready
PyTorch, JAX, and Triton. Model architecture and Training Methodology Claude Haiku 4.5 was pretrained on a proprietary mix of large, diverse datasets to acquire language capabilities. After the pretraining process, th... PyTorch, JAX, and Triton. Model architecture and Training Methodology Claude Haiku 4.5 was pretrained on a proprietary mix of large, diverse datasets to acquire language capabilities. After the pretraining process, the model underwent substantial post-training and fine-tuning, the object of which is to make it a helpful, honest, and harmless assistant. This involves a variety of techniques, including reinforcement le
Full README
PyTorch, JAX, and Triton. Model architecture and Training Methodology Claude Haiku 4.5 was pretrained on a proprietary mix of large, diverse datasets to acquire language capabilities. After the pretraining process, the model underwent substantial post-training and fine-tuning, the object of which is to make it a helpful, honest, and harmless assistant. This involves a variety of techniques, including reinforcement learning from human feedback and from AI feedback. Training Data Claude Haiku 4.5 was trained on a proprietary mix of publicly available information on the Internet as of February 2025, non-public data from third parties, data provided by data-labeling services and paid contractors, data from Claude users who have opted in to have their data used for training, and data we generated internally at Anthropic. Testing Methods and Results Based on our assessments of the model’s dem
API & Reliability
Machine endpoints, contract coverage, trust signals, runtime metrics, benchmarks, and guardrails for agent-to-agent use.
MissingGITHUB REPOS
API & Reliability
Machine endpoints, contract coverage, trust signals, runtime metrics, benchmarks, and guardrails for agent-to-agent use.
Machine interfaces
Contract & API
Contract coverage
Status
missing
Auth
None
Streaming
No
Data region
Unspecified
Protocol support
Requires: none
Forbidden: none
Guardrails
Operational confidence: low
Invocation examples
curl -s "https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/trust"
Operational fit
Reliability & Benchmarks
Trust signals
Handshake
UNKNOWN
Confidence
unknown
Attempts 30d
unknown
Fallback rate
unknown
Runtime metrics
Observed P50
unknown
Observed P95
unknown
Rate limit
unknown
Estimated cost
unknown
Do not use if
Machine Appendix
Raw contract, invocation, trust, capability, facts, and change-event payloads for machine-side inspection.
MissingGITHUB REPOS
Machine Appendix
Raw contract, invocation, trust, capability, facts, and change-event payloads for machine-side inspection.
Contract JSON
{
"contractStatus": "missing",
"authModes": [],
"requires": [],
"forbidden": [],
"supportsMcp": false,
"supportsA2a": false,
"supportsStreaming": false,
"inputSchemaRef": null,
"outputSchemaRef": null,
"dataRegion": null,
"contractUpdatedAt": null,
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Invocation Guide
{
"preferredApi": {
"snapshotUrl": "https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/snapshot",
"contractUrl": "https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/contract",
"trustUrl": "https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/trust"
},
"curlExamples": [
"curl -s \"https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/snapshot\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/contract\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": []
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "GITHUB_REPOS",
"generatedAt": "2026-10-09T03:38:00.925Z"
}
},
"retryPolicy": {
"maxAttempts": 3,
"backoffMs": [
500,
1500,
3500
],
"retryableConditions": [
"HTTP_429",
"HTTP_503",
"NETWORK_TIMEOUT"
]
}
}Trust JSON
{
"status": "unavailable",
"handshakeStatus": "UNKNOWN",
"verificationFreshnessHours": null,
"reputationScore": null,
"p95LatencyMs": null,
"successRate30d": null,
"fallbackRate": null,
"attempts30d": null,
"trustUpdatedAt": null,
"trustConfidence": "unknown",
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Capability Matrix
{
"rows": [],
"flattenedTokens": ""
}Facts JSON
[
{
"factKey": "vendor",
"category": "vendor",
"label": "Vendor",
"value": "Anthropic",
"href": "https://www.anthropic.com/transparency",
"sourceUrl": "https://www.anthropic.com/transparency",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-14T23:26:25.608Z",
"isPublic": true
},
{
"factKey": "docs_crawl",
"category": "integration",
"label": "Crawlable docs",
"value": "6 indexed pages on the official domain",
"href": "https://anthropic.com/privacy",
"sourceUrl": "https://anthropic.com/privacy",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-03-14T02:03:15.219Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/trust",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/crawl-b9e7915be186b2b9ba1d-ebb7309384b304f5115d/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true
}
]Change Events JSON
[
{
"eventType": "docs_update",
"title": "Docs refreshed",
"description": "Fresh crawlable documentation was indexed for the official domain.",
"href": "https://anthropic.com/privacy",
"sourceUrl": "https://anthropic.com/privacy",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-03-14T02:03:15.219Z",
"isPublic": true
}
]