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SKILL verified MIT Self-run

Chainlink Confidential Ai Attester Skill

skill-smartcontractkit-chainlink-agent-skills-chainlink-confidential-ai-attester-skill · by smartcontractkit

Chainlink Confidential AI Attester: submit private documents to an LLM inside an AWS Nitro Enclave and get back a cryptographically attested result — raw documents never leave the TEE. Use for these hackathon scenarios: (1) undercollateralized DeFi lending — upload a bank statement, get an attested approved/denied JSON decision without exposing financials on-chain; (2) accredited investor verific…

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Install

$ agentstack add skill-smartcontractkit-chainlink-agent-skills-chainlink-confidential-ai-attester-skill

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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1mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

Chainlink Confidential AI Attester

Runs LLM inference inside Trusted Execution Environment (TEE). Documents go in, LLM analysis comes out — the raw documents are never stored or exposed.

Beta product for the EthGlobal NYC hackathon. Get an API key at the Chainlink booth or via the #partner-chainlink channel in the EthGlobal Discord.

Playground UI: https://confidential-ai-dev-preview.cldev.cloud/playground — easiest way to try it. Everything there maps 1:1 to the API calls below.


Workflow 1 — Submit: POST /v1/inference

Auth: Authorization: Bearer $API_KEY — always use an env var, never hardcode.

Request shape:

{
  "model": "gemma4",
  "system_prompt": "",
  "prompt": "...",
  "resources": [{ "filename": "doc.pdf", "content_type": "application/pdf", "content_base64": "" }],
  "cre_callback": { "url": "https://..." }
}
  • cre_callback is optional — omit it and poll instead.
  • Models: gemma4 (images/general, default), qwen3.6 (long text).
  • Prefer PNG over PDF for demos — PDF preprocessing can take up to 5 minutes.

Response: 202 Accepted{ "id": "...", "status": "queued" } — save the id.

For curl examples and multi-language snippets → [references/code-examples.md](references/code-examples.md) For full request/response spec, error codes, resource types → [references/api-reference.md](references/api-reference.md)


Workflow 2 — Poll: GET /v1/inference/{id}

Poll every 2–5 s until status is completed or failed.

Key fields on completion: output (LLM text), usage, completed_at.

For error symptoms → [references/troubleshooting.md](references/troubleshooting.md)


Writing Prompts That Work

Always enforce JSON output with two layers:

  1. System prompt — keep the default unless you have a specific reason to change it.
  2. User prompt — binary question + exact JSON schema to return

For per-use-case prompt templates (lending, KYC, accredited investor, proof of reserves) → [references/prompts.md](references/prompts.md)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.