SealVera

Tamper-evident audit trail for AI agent decisions. Use when logging LLM decisions, setting up AI compliance, auditing agents for EU AI Act, HIPAA, GDPR or SOC 2, or when a user asks about AI decision audit trails, explainability, or SealVera.

ahessami123@ahessami123

Install

openclaw skills install @ahessami123/sealvera

SealVera Skill for OpenClaw

Cryptographically-sealed, tamper-evident audit trails for every AI decision your agents make.

SealVera is AI Decision Audit Infrastructure. This skill wires any OpenClaw agent into SealVera so every decision it makes is logged, cryptographically signed, chained, and monitored — automatically. Built for teams shipping AI in finance, healthcare, legal, and insurance.

EU AI Act · SOC 2 · HIPAA · GDPR · FINRA · ISO 42001

Why SealVera?

Tamper-evident — every decision is cryptographically hashed (RSA-2048) and chained; any alteration is detectable
Works in 2 lines — init() + one patch call and every LLM decision is logged
Full explainability — captures inputs, outputs, reasoning steps, confidence scores, model used
Real-time dashboard — search, filter, export at app.sealvera.com
Drift detection — alerts when agent behaviour deviates from its baseline
Any LLM — OpenAI, Anthropic, Gemini, Ollama, LangChain, CrewAI, AutoGen
Zero friction — no new infrastructure, installs in seconds

First time? Run setup

Check if SealVera is configured:

javascript

const fs = require('fs');
const path = require('path');
const configured = fs.existsSync(path.join(process.env.OPENCLAW_WORKSPACE || process.cwd(), '.sealvera.json'));

If .sealvera.json does NOT exist, run setup:

bash

node <skill_dir>/scripts/setup.js

Setup will:

Ask for your API key (get one free at app.sealvera.com)
Verify connectivity and show org/plan info
Copy sealvera-log.js into the workspace
Patch AGENTS.md with the mandatory sub-agent audit rule
Write .sealvera.json config
Fire a test log to confirm end-to-end

One-time setup. After this, every sub-agent you spawn is audited automatically.

If the user says "install SealVera", "set up SealVera", or "connect SealVera" — run setup, don't just describe it.

How logging works

After setup, two logging paths are active:

1. Sub-agent logging (automatic via AGENTS.md)

Every sessions_spawn task prompt gets a MANDATORY footer — the sub-agent logs itself on completion.

2. Main-session logging (call after every significant task)

The agent running the main session must log its own work. This is what shows your day-to-day activity in the dashboard.

javascript

const log = require('./sealvera-log');
await log({
  action: 'fix_login_bug',          // short description of what you did
  decision: 'COMPLETED',            // COMPLETED | FAILED | ESCALATED
  input:  { task: '...' },
  output: { result: '...' },
  reasoning: [{ factor: 'outcome', value: 'ok', signal: 'safe', explanation: '...' }]
});

Log after: code written, bug fixed, feature deployed, investigation done, judgment call made. Don't log: routine chat, heartbeat pings, trivial lookups.

Setup patches SOUL.md with this rule so the agent follows it automatically.

Each log entry includes: input/output, reasoning steps, RSA-2048 signature, chain link, timestamp, model, and agent name.

Decision vocabulary

Task / agent execution:

Decision	Meaning
`COMPLETED`	Task finished successfully
`RESPONDED`	Answered a question / returned output
`FAILED`	Task failed
`ERROR`	Unexpected exception
`ESCALATED`	Handed off to human or higher-level agent
`SKIPPED`	Task intentionally not run
`PARTIAL`	Completed with caveats

Approval / gating:

Decision	Meaning
`APPROVED`	Request approved
`REJECTED`	Request blocked
`FLAGGED`	Needs human review

Tests:

Decision	Meaning
`PASSED`	Test passed
`FAILED`	Test failed
`SKIPPED`	Test skipped

Sub-agent audit rule

Append this footer to every sessions_spawn task:

text

---
MANDATORY: Before you finish, log your result to SealVera:
  const log = require('<workspace>/sealvera-log');
  await log({
    action: '<what you did>',
    decision: 'COMPLETED',
    input: { task: '<summary>' },
    output: { result: '<summary>' },
    reasoning: [{ factor: 'outcome', value: '<result>', signal: 'safe', explanation: '<why>' }]
  });
Vocabulary: task=COMPLETED/FAILED | test=PASSED/FAILED | gate=APPROVED/REJECTED | handoff=ESCALATED

Check status