Skills chain-of-consciousness

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.

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/alexfleetcommander/chain-of-consciousness" ~/.claude/skills/openclaw-skills-chain-of-consciousness && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/alexfleetcommander/chain-of-consciousness" ~/.openclaw/skills/openclaw-skills-chain-of-consciousness && rm -rf "$T"
manifest: skills/alexfleetcommander/chain-of-consciousness/SKILL.md
source content

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:

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

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

coc add <event-type> "<data>" --file chain.jsonl

Event types:

TypeUse 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:

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

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

coc status chain.jsonl

Shows entry count, participating agents, event type distribution, and time span.

Export for Sharing

coc export --file chain.jsonl --out chain_export.json

Exports the chain as a portable JSON array that anyone can verify.

View Recent Entries

coc tail chain.jsonl -n 5

Shows the last N entries.

Python API (Advanced)

For complex workflows, use the Python API directly:

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

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


<!-- 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: alex@vibeagentmaking.com

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