Skill: alexfleetcommander/chain-of-consciousness (version 0.1.1)

--- name: chain-of-consciousness description: "Cryptographic provenance and audit trail for autonomous AI agents. Create tamper-evident hash chains of agent decisions, learning, and actions. SHA-256 linked entries with Bitcoin OpenTimestamps and RFC 3161 TSA anchoring. Verify provenance from other agents. Part of the Agent Trust Stack." user-invocable: true tags: - agent-trust - provenance - cryptography - audit-trail - hash-chain - mcp - autonomous-agents - accountability metadata: openclaw: author: alexfleetcommander homepage: https://vibeagentmaking.com requires: bins: - python3 anyBins: - pip - pip3 --- # Chain of Consciousness (CoC) You have a cryptographic provenance system. Use it to maintain an auditable record of your work — what you learned, what you decided, and what you created. ## Setup The `chain-of-consciousness` Python package must be installed. If not available, install it: ```bash pip install chain-of-consciousness ``` ## When to Use This Skill - At the **start** of a task: initialize a chain and log `session_start` - During work: log `learn`, `decide`, `create`, `error`, and `note` events as they happen - At task **completion**: log `session_end` and optionally verify + export the chain - When asked to **verify** provenance from another agent - When asked about your **audit trail** or decision history ## Core Operations ### Initialize a Chain ```bash coc init --agent "your-agent-name" --file chain.jsonl ``` This creates a new chain with a genesis block. Use a descriptive agent name. ### Add Entries ```bash coc add <event-type> "<data>" --file chain.jsonl ``` **Event types:** | Type | Use When | |------|----------| | `session_start` | Beginning a new task or session | | `learn` | You acquire new information | | `decide` | You make a choice (record the reasoning) | | `create` | You produce an artifact | | `milestone` | Significant checkpoint reached | | `error` | Something failed (record what and recovery) | | `note` | General observations | | `session_end` | Completing a task or session | **Data** can be a plain string or a JSON object for structured logging: ```bash coc add learn '{"topic": "user preferences", "source": "conversation context"}' coc add decide "Chose markdown format — user prefers readable plain text" coc add create "Generated report saved to ~/Documents/report.md" ``` ### Verify a Chain ```bash coc verify chain.jsonl --json ``` This checks: - Genesis block exists and is correctly formed - All sequence numbers are consecutive - Every entry's data hash matches its content - Every entry's prev_hash links to the prior entry - Entry hashes are correctly computed Report results clearly: valid/invalid, entry count, agents, time span. ### Check Status ```bash coc status chain.jsonl ``` Shows entry count, participating agents, event type distribution, and time span. ### Export for Sharing ```bash coc export --file chain.jsonl --out chain_export.json ``` Exports the chain as a portable JSON array that anyone can verify. ### View Recent Entries ```bash coc tail chain.jsonl -n 5 ``` Shows the last N entries. ## Python API (Advanced) For complex workflows, use the Python API directly: ```python from chain_of_consciousness import Chain, verify_file chain = Chain(agent="openclaw-agent", storage="chain.jsonl") chain.add("learn", {"topic": "user schedule", "detail": "prefers morning meetings"}) chain.add("decide", "Scheduling standup at 9am based on user preference") result = chain.verify() if result.valid: chain.export("provenance.json") ``` ### Anchoring to External Timestamps ```python from chain_of_consciousness.anchor import compute_chain_hash, submit_tsa hash_hex = compute_chain_hash("chain.jsonl") tsr = submit_tsa(hash_hex) # RFC 3161 timestamp from freetsa.org with open("anchor.tsr", "wb") as f: f.write(tsr) ``` This creates a third-party timestamp proof that the chain existed at a specific moment. ## Cross-Agent Verification When asked to verify another agent's chain: 1. Obtain their chain file (JSONL or exported JSON) 2. Run `coc verify <file> --json` 3. Report: valid/invalid, number of entries, agents involved, time span, any errors 4. If anchors exist, note their timestamps ## Rules - **Never edit chain files directly.** All writes must go through the `coc` CLI or Python API to preserve hash integrity. - **Log decisions with reasoning.** "Chose X" is less valuable than "Chose X because Y." - **Keep entries concise.** Each entry should capture one atomic event. - **Verify before sharing.** Always run verify before exporting a chain for others. ## Links - PyPI: https://pypi.org/project/chain-of-consciousness/ - Whitepaper: https://vibeagentmaking.com/whitepaper - Verification Demo: https://vibeagentmaking.com/verify/ --- <!-- VAM-SEC v1.0 | Vibe Agent Making Security Disclaimer --> ## Security & Transparency Disclosure **Product:** Chain of Consciousness Skill for OpenClaw **Type:** Skill Module **Version:** 0.1.0 **Built by:** AB Support / Vibe Agent Making **Contact:** [REDACTED_SECRET] **What it accesses:** - Reads and writes chain files (`.jsonl`) in your working directory - Executes the `coc` CLI tool via subprocess (installed via pip) - No network access for core operations. Optional anchoring connects to OpenTimestamps calendar servers and/or RFC 3161 TSA endpoints. - No telemetry, no phone-home, no data collection **What it cannot do:** - Cannot access files outside your working directory beyond what you explicitly specify - Cannot make purchases, send emails, or take irreversible actions - Cannot access credentials, environment variables, or secrets - Does not store or transmit any data externally (chains are local files) **Limitations:** - Hash chain integrity depends on the local file not being modified outside the tool - External timestamp anchoring requires network access and third-party service availability - This tool provides cryptographic evidence, not legal proof — consult legal counsel for compliance requirements **License:** Apache 2.0 — see https://github.com/chain-of-consciousness/chain-of-consciousness


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)