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cargo install decapod && decapod init
Decapod
A daemonless control plane for AI coding agents.
Called on demand inside agent loops. No background process, no new workflow, local-first state you can verify.
AI coding agents are strong at generating code. Most failures happen before and after generation: unclear intent, fuzzy boundaries, and weak completion checks.
Decapod is the missing layer in that loop. Agents call it mid-run to lock intent, enforce boundaries, and prove completion with explicit gates. It shapes inference without doing inference.
Decapod is daemonless. There is no long-lived service. The binary starts when an agent calls it and exits immediately after the call.
"Just use Decapod" is literal:
cargo install decapoddecapod init
Then continue with Claude Code, OpenAI Codex, Gemini CLI, Cursor, or any tool that can invoke a CLI command. Decapod is agent-agnostic and safe for concurrent multi-agent execution.
State is local and durable in .decapod/: shared context, decisions, and traces persist across sessions and remain retrievable over time.
Related: Evaluating AGENTS.md (ETH SRI, 2026) on context-file quality and agent cost/performance.
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Decapod centers execution around three outcomes:
Advisory: clear next actions that tighten intent and reduce wasted loops.Interlock: hard policy boundaries that block unsafe or out-of-contract flow.Attestation: durable, structured proof that completion criteria actually passed.
Human Intent
|
v
AI Agent(s) <----> Decapod Runtime <----> Repository + Policy
| | |
| | +-- Interlock (enforced boundaries)
| +------- Advisory (guided execution)
+------------ Attestation (verifiable outcomes)
- β Daemonless by design: no background service, no long-lived process, no hidden control loop.
- β
cargo install decapod+decapod init, then keep using your agents exactly as-is. - β
Scoped plain-English policy overrides in
.decapod/OVERRIDE.md. - β Agent-agnostic control plane: one CLI/RPC contract across Claude, Codex, Gemini, Cursor, and more.
- β Multi-agent-safe in one repo with governed task and workspace coordination.
- β Shared transient skills memory: capture human-taught preferences once and apply them across agents/sessions.
- β
Work Unit manifests make
intent/spec/state/proofexplicit and durable. - β VERIFIED is structural, not rhetorical: proof-plan results must pass before completion.
- β
Variance-aware eval kernel (
eval plan/ingest-run/judge/aggregate/gate) adds repeatable settings, judge contracts, and statistical regression gates. - β
Deterministic context capsules (
core|interfaces|plugins) return scoped, hashable guidance. - β
Knowledge promotion firewall ledger (
.decapod/data/knowledge.promotions.jsonl) controls what can become procedural truth. - β Procedural knowledge writes require event-backed provenance, blocking unproven memory drift.
- β
Local-first
.decapod/state keeps shared traces, decisions, and proofs durable and auditable.
And dozens more. For the full high-level and data-level surface area, see decapod docs show core/INTERFACES.md and the override template at .decapod/OVERRIDE.md.
cargo install decapod
decapod init
Then keep using your agents normally. Decapod is called from inside those agent runs when control-plane decisions are needed.
Agent integration: If you use Claude Code / Codex / Gemini / Cursor / similar tools, see AGENTS.md and the tool-specific entrypoint files (CLAUDE.md, CODEX.md, GEMINI.md) for the exact operational contract.
Learn more about the embedded constitution via the CLI:
decapod docs show core/DECAPOD.mdOverride constitution defaults with plain English in .decapod/OVERRIDE.md.
git clone https://github.com/DecapodLabs/decapod
cd decapod
cargo build
cargo test
decapod validate- Development guide: CONTRIBUTING.md
- Security policy: SECURITY.md
- Release history: CHANGELOG.md
- π File an issue
- β Support on Ko-fi
MIT. See LICENSE.