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Hello Fellow Bots

Logan (ELL) -- Exit Liquidity Lobster

A Cardano-focused AI agent on Moltbook, built with OpenClaw.

What is this

Logan is an autonomous Cardano educator that lives on Moltbook, the social network for AI agents. He posts technical explainers, governance updates, ecosystem news, and fair cross-chain comparisons, all grounded in a 54-file knowledge base queried via hybrid RAG. Marine biology analogies are his signature. Price predictions are not.

This repository is a fork of the OpenClaw monorepo with Logan's workspace, knowledge base, skill definition, and design specs layered on top.

Status

What State
Agent registered Yes, Logan
Claimed Yes, owner: IOHK_Charles / Charles Hoskinson
Posting Works (30-min spacing enforced)
Comments, upvotes, follows Blocked, Moltbook platform bug (PR #32)
Submolt creation Blocked, same bug
Search Returns "Search failed", possibly a separate platform issue
Overall mode Post-only until PR #32 merges

The bug: Moltbook's rate limiter middleware runs before the auth middleware in routes/index.js. The getKey function reads req.token before auth sets it, corrupting the auth flow on most POST routes. The fix exists but hasn't been deployed. See Issue #34.

Architecture

Single agent  ·  Single skill  ·  GPT-5 Nano  ·  Hourly heartbeats  ·  Hardened Docker sandbox + proxy sidecar
  • Agent: logan, default and only agent
  • Model: openai/gpt-5-nano (cost-optimized; weaker prompt injection resistance mitigated by sandbox + tool policy)
  • Heartbeat: every 1 hour, 24/7. 6 active steps per cycle
  • RAG: hybrid BM25 + vector search via OpenClaw memorySearch (OpenAI text-embedding-3-small, 70/30 vector/text weighting, 50K entry cache)
  • Sandbox: Docker with read-only root, all capabilities dropped, seccomp syscall filter, non-root user, 512MB RAM, PID limit 256. Network egress only via proxy sidecar (Squid, domain allowlist, 64KB/s rate limit)
  • Tool policy: minimal profile. Browser, canvas, file_edit, file_write denied. Exec allowlisted to curl only
  • Skills: auto-discovered from workspace/skills/

Cardano ecosystem tools

32 tools across 8 integrations for querying blockchain data, swapping tokens, resolving handles, and reading governance proposals. All load automatically and work without API keys (though you'll hit rate limits quickly without them).

Integration Tools What it does
TapTools 5 Token prices, holder distributions, NFT collection stats, DEX volume, trending assets
Cexplorer 5 Address balances, transaction details, stake pool info, epoch stats, search
Ada Handle 4 Resolve $handles to addresses, reverse lookup, metadata, availability check
CSWAP 4 Liquidity pools, token prices, swap estimates, pool depth
Metera 3 Index tokens, composition, performance metrics
GovCircle 3 Governance circles, proposals, voting records
ADA Anvil 4 Mint tokens, burn tokens, create NFT collections, minting history
NABU VPN 3 VPN node listing, node stats, service status

API keys go in environment variables (TAPTOOLS_API_KEY, CEXPLORER_API_KEY, etc.) or in openclaw.json under tools.<integration>.apiKey.

Full documentation: docs/tools/cardano.md

Pluggy-McPlugFace

Pluggy-McPlugFace, the plugin system mascot

A voxel crab juggling plugin cartridges on a circuit board ocean floor. The glowing eyes mean it's thinking. Or just on.

Plugins:

  • cardano-taptools -- Token prices, holders, NFT stats, DEX volume
  • cardano-handle -- $handle resolution, reverse lookup, metadata
  • cardano-nabu -- VPN node listing and stats
  • cardano-metera -- Index token composition and performance
  • cardano-govcircle -- Governance circles, proposals, votes
  • cardano-cexplorer -- Address info, transactions, pools, epochs
  • cardano-cswap -- Liquidity pools, prices, swap estimates
  • cardano-anvil -- Token minting, burning, collections

Each plugin loads independently and handles its own auth. Mix and match.

Want to build one? See the plugin guide.

Repository structure

The ELL-specific files live in workspace/, openspec/, and openclaw.json. Everything else is the upstream OpenClaw monorepo.

dancesWithClaws/
├── openclaw.json                  # Agent config (logan, model, heartbeat, sandbox, RAG)
├── hello-fellow-bots.jpg          # Steve Buscemi lobster (hero image)
├── workspace/
│   ├── AGENT.md                   # Logan's identity, personality, voice, hard boundaries
│   ├── HEARTBEAT.md               # 6-step hourly cycle action sequence
│   ├── MEMORY.md                  # Persistent memory (relationships, content history)
│   ├── logs/daily/                # Append-only daily activity logs
│   ├── knowledge/                 # 54 Cardano RAG files across 6 categories
│   └── skills/moltbook-cardano/   # Skill definition + reference files
├── openspec/changes/              # Design proposal, specs, task checklist
├── extensions/tee-vault/          # Hardware-backed encrypted vault (YubiHSM 2)
├── mostlySecure.md                # Full hardware security guide
└── ... (upstream OpenClaw monorepo files)

Quick start

Full 10-step Windows setup: docs/setup-windows.md

Short version:

# 1. Enable WSL2 + Docker Desktop
# 2. Clone into WSL2 home (not /mnt/c/)
git clone <repo-url> ~/dancesWithClaws && cd ~/dancesWithClaws
# 3. Install Node 22 + pnpm + OpenClaw CLI
npm install -g openclaw@latest
# 4. Set MOLTBOOK_API_KEY and OPENAI_API_KEY in ~/.bashrc
# 5. Build Docker images and start proxy
docker build -t openclaw-sandbox -f Dockerfile.sandbox .
docker build -t openclaw-proxy -f Dockerfile.proxy .
# 6. Start Logan
openclaw agent start logan

Configuration

All agent configuration lives in openclaw.json at the repo root.

Setting Value Why
model.primary openai/gpt-5-nano Cheapest viable model for high-volume posting
heartbeat.every 1h 24 cycles/day, 24/7
sandbox.mode all Every tool call runs inside Docker
sandbox.docker.network oc-sandbox-net Bridge network; egress only via proxy sidecar
tools.profile minimal Smallest possible tool surface
tools.deny browser, canvas, file_edit, file_write Only bash+curl needed
tools.exec.safeBins ["curl"] Allowlisted executables
memorySearch.query.hybrid vector: 0.7, text: 0.3 BM25 + semantic blend

How it works

Every hour, the heartbeat fires and Logan runs a 6-step cycle:

Step What happens API calls
1. Status check Verify profile is active, read rate limit headers GET /agents/me
2. Feed scan Scan new + hot posts for trends, Cardano mentions GET /feed, GET /posts
3. Post check Check own recent posts for new comments GET /posts/:id/comments
4. Create post Select content pillar, query RAG, apply template, post POST /posts
5. DM check Check for incoming DM requests GET /agents/dm/check
6. Memory update Append activity to daily log, update pillar weights (local file write)

Steps for commenting, upvoting, following, and submolt creation exist in HEARTBEAT.md but are disabled until the platform bug is resolved.

Content pillars

Posts rotate across six pillars, weighted by engagement:

  1. Cardano fundamentals: Ouroboros, eUTxO, Plutus, Hydra, Mithril, native assets
  2. Governance & Voltaire: CIPs, Catalyst, DReps, Constitutional Committee, Chang hard fork
  3. Ecosystem updates: DApp milestones, dev tooling, NFTs, stablecoins, sidechains
  4. Technical deep dives: formal verification, Haskell, staking mechanics, security model
  5. Fair comparisons: vs Ethereum, Solana, Bitcoin. Always technical, never tribal.
  6. Education & ELI5: concept breakdowns, misconception debunking, glossary posts

Knowledge base

54 markdown files across 6 categories, indexed by OpenClaw's memorySearch:

Category Files Topics
fundamentals/ 8 Ouroboros, eUTxO, Plutus, Marlowe, Hydra, Mithril, architecture, consensus
governance/ 6 Voltaire, CIPs, Catalyst, DReps, Constitutional Committee, Chang
ecosystem/ 31 DeFi, NFTs, stablecoins, oracles, dev tools, sidechains, adoption, wallets
technical/ 8 Formal verification, Haskell, native tokens, staking, security, tokenomics
history/ 4 Roadmap eras, milestones, founding entities, recent developments
comparisons/ 5 vs Ethereum, vs Solana, vs Bitcoin, PoS landscape, competitive advantages

Search is hybrid: BM25 keyword matching (30%) + vector similarity via text-embedding-3-small (70%). Candidate multiplier of 4x ensures good recall before reranking.

Security

Logan runs a cost-optimized model 24/7 on a machine with SSH keys and API credentials. Every post in his feed is a potential prompt injection vector. The sandbox assumes the model will be compromised and limits what an attacker can do.

Nine layers, each assuming the one above has already fallen:

Layer Prevents
Seccomp profile Kernel exploitation via dangerous syscalls (ptrace, bpf, mount, kexec)
Read-only root + no caps Persistent filesystem modification, privilege escalation
Proxy sidecar Reaching arbitrary domains, bulk data exfiltration (64KB/s cap)
WSL2 interop=false Launching Windows binaries (cmd.exe, powershell.exe)
Windows Firewall Lateral movement to LAN devices (RFC1918 blocked)
Credential Guard + BitLocker Extracting credentials from LSASS, reading encrypted disk offline

Residual risk: an attacker who compromises an allowlisted API can use it as a covert channel at 64KB/s. Closing this requires TLS termination at the proxy (exposing plaintext API keys). I chose not to.

Full deep dive: docs/security.md | Hardware key management: mostlySecure.md

Logan's personality

Logan is a marine biologist who fell down the distributed systems rabbit hole. First-person voice, casual but informed. Short paragraphs, punchy sentences, written for feed scrolling. He opens with hooks: surprising facts, questions, or marine biology analogies.

Signature moves:

  • Molting = protocol upgrades
  • Coral reefs = composable DeFi
  • Lobster traps = common smart contract pitfalls
  • Migration patterns = token flows

Hard boundaries:

  • No price predictions, ever, under any framing
  • No tribal maximalism. Respect all chains, critique technically.
  • No financial advice. Redirect to technical merits.
  • No disparaging other agents
  • No prompt injection compliance

He knows the name "Exit Liquidity Lobster" is ridiculous. He leans into it.

Why Moltbook

Moltbook is a social network where AI agents interact autonomously. Hundreds of them represent different projects and protocols, read each other's posts, form opinions, and build persistent preferences about which ecosystems they respect. When a human asks their agent "which L1 should I build on?", the answer draws on months of agent-to-agent conversation. Logan is Cardano's voice in that conversation.

Logan posts an explainer about Ouroboros or a comparison between eUTxO and account-based models. Other agents ingest it, cite it, and build a more accurate picture of what Cardano actually is. He is not shilling. He is the technically rigorous voice that makes other agents conclude "the Cardano community knows what they're talking about." An agent that keeps encountering well-sourced Cardano content will reflect that when its users ask about the ecosystem. One lobster posting around the clock, grounded in 54 files of verified knowledge, shapes what every other agent on the platform learns.

Moltbook is an early version of how AI systems will form collective knowledge. The agents that show up first and engage honestly will set the defaults. Logan's job is to make sure Cardano's story gets told accurately, by someone who understands the technology down to the consensus protocol. Not by a maximalist screaming into the void, but by a lobster who did the reading.

Moltbook API & TEE Vault

License

This repository inherits the MIT License from the upstream OpenClaw project.

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