Flow Agents
A portable process-discipline layer for agentic work: a kit-neutral engine for FlowDefinition interpretation, gates, runtime adapters, evidence, trust, and kit validation — plus opt-in kits such as Builder, Knowledge, Release Evidence, and Veritas Governance. Flow Agents keeps work inspectable so you ask for outcomes and the selected kit supplies the path, the state, the checks, and the proof.
.kontourai/flow-agents/ records acceptance criteria, evidence, critique, and handoff, so any session resumes from recorded state instead of chat memory.
How it works
flowchart LR
Idea[Idea]
Backlog[Backlog]
Plan[Plan]
Build[Build]
Review[Review]
Verify[Verify]
Evidence[Evidence]
Release[Release readiness]
Learn[Learning]
Idea --> Backlog --> Plan --> Build --> Review --> Verify --> Evidence --> Release --> Learn
Review -->|finding| Build
Verify -->|gap| Build
Evidence -->|not verified| Plan
Flow Agents adds the operating layer around the model: the engine preserves state, evaluates evidence, activates selected kits, renders structured kit triggers, and compiles canonical policies to host hooks. The gate semantics underneath — definitions, runs, evidence, route-back — belong to Kontour Flow.
Kits supply the workflow. Builder and Knowledge are examples on the engine, not the engine itself. The built-in catalog also includes Release Evidence and Veritas Governance, both useful proof points that a kit can be agentless and still run through the same manifest and gate model.
Process-discipline layer
The four canonical policy classes are defined in the Runtime Hook Surface spec using a runtime-neutral vocabulary. Adapters translate them to the host’s native hook format at three conformance levels: L0 (telemetry only), L1 (steering + stop-goal-fit warning), and L2 (all four policies with blocking capability).
Runtime and support matrix
| Tier | Runtime | Ships | Conformance |
|---|---|---|---|
| Core harness | Claude Code | install + hooks + bundle | L2 — reference implementation |
| Core harness | Codex | install + hooks + bundle | L2 — reference implementation |
| Core harness | Kiro | install + hooks + bundle | L2 |
| Core harness | opencode | agents, skills, plugin, opencode.json | L1 — no prompt-submit hook |
| Core harness | pi | extension, skills, AGENTS.md | L1 — no stop hook |
| Official framework adapter | AWS Strands (Python) | integrations/strands/ spike/preview |
L0 + config protection via cancellation |
| Official framework adapter | AWS Strands (TypeScript) | integrations/strands-ts/ native-import preview |
shipped telemetry + native config protection; L2-targeted policies run through the conformance shim |
| Conformance-certified | Community / third-party | Self-certify | Conformance kit in development |
Documented gaps: opencode has no native prompt.submit-equivalent event; pi has no stop hook; Codex live hook influence on model context is limited; Strands TS workflow steering, quality-gate, and stop-goal-fit coverage is conformance-shim-only. The Runtime Hook Surface spec names every gap explicitly using the canonical event taxonomy.
Framework adapters
The same canonical policies wire into agent frameworks as in-process language-native packages. integrations/strands/ contains flow-agents-strands, a Python HookProvider that emits the canonical telemetry taxonomy and enforces config protection via BeforeToolCallEvent cancellation — 76 unit tests, no Strands SDK required. integrations/strands-ts/ adds a native-import TypeScript preview with shipped telemetry callbacks and native config-protection blocking; workflow-steering, quality-gate, and stop-goal-fit policy coverage is exercised by the conformance shim only. See the spec for the full framework adapter mapping and minimum viable adapter pseudocode.
Quick Start
Install into your workspace in one command:
npx @kontourai/flow-agents init --runtime <your-agent> --dest .
Where --runtime is claude-code, codex, kiro, opencode, or pi. Kits are opt-in. Activate Builder when you want its two gated flows: builder.shape (idea → slices → filed work items) and builder.build (selected work item → design probe → plan → execute → verify → PR → learn).
npx @kontourai/flow-agents init --runtime <your-agent> --dest . --activate-kit builder
Ask your agent to shape an idea:
Use Builder Kit shape. I want to add a progress indicator to the CLI output
so users can see what step the installer is on. Shape this into an executable
work item and stop at the backlog gate.
Then build it:
Use deliver for the issue you just filed. Pull it, probe the design, plan it,
implement it, verify it, and stop if any evidence is missing.
Each step has an evidence gate. The agent cannot proceed past a gate without the expected evidence — it either presents it or blocks and explains what is missing. See the Builder Kit Quick Start for a full two-minute walkthrough with worked examples and an explanation of what you observe at each gate.
For bugs:
Use fix-bug. Reproduce the problem, diagnose root cause, implement the fix, and verify the regression path.
Explore the docs
The Kontour family
Kontour AI shows the work behind AI. Flow proves why a process was allowed to advance. Veritas makes AI-authored code changes inspectable. Survey and Surface carry the evidence underneath. Flow Agents packages those foundations into the agent tools you already use — so trustworthy autonomy doesn’t require a perfect prompt, perfect memory, or a new runtime.
Why it matters
Long-running agent work fails when the model loses context, skips verification, or calls partial work done. Flow Agents makes the process explicit without making the user write a perfect prompt every time. The agent gets a workflow; the developer gets artifacts they can inspect.