Flow SpecKit
Durable, artifact-driven AI-SDLC workflow orchestration — think "Temporal for AI Software Engineering".
Flow SpecKit orchestrates the complete AI-assisted software development lifecycle, not just the coding step:
Business Idea → Discovery → Product Shaping → Technical Design
→ Implementation → Review → Merge → Release
Durable, resumable workflows drive stateless AI skills and pluggable coding agents (Claude Code, Cursor, …), with human approval gates owning every consequential transition and every phase producing a versioned, lineage-linked artifact.
Status: early development. Phase 2 (Artifact Engine) is complete; Phase 3 (Workflow Engine) is in progress. The full wedge demo below is the v0.1 target, not yet functional end to end.
Install
pip install flow-speckit
The wedge (v0.1 target demo)
In any existing repository, with nothing installed but Python and a coding-agent CLI:
$ flow-speckit init
$ flow-speckit run feature --idea "Add CSV export to the reports page"
which durably executes:
FrameBrief → [human gate: approve brief] → ProductArtifact → TechnicalDesign
→ [human gate: approve design] → Claude Code implements in an isolated
git worktree → Pull request opened
Three properties no prompt-first tool can offer:
- Durability —
kill -9the process mid-implementation, thenflow-speckit resumecontinues exactly where it stopped. - Lineage —
flow-speckit trace <pr-url>prints the full provenance of the PR back to the business idea: every artifact version, who approved what and when, and per-step token cost. - Accountability — the append-only event log proves the workflow, not the model, decided every transition; humans resolved every gate.
Core principles
- Artifact-driven — every phase consumes an artifact and produces a new, versioned, schema-validated artifact. Artifacts, never chat history, are the source of truth.
- Workflow-first — a durable state machine owns all transitions. AI never picks the next step.
- Stateless skills — every AI capability is a stateless, independently executable skill. No long-running autonomous agents.
- Human gates — approval gates are first-class workflow states. Humans own decisions; AI owns artifacts.
- Pluggable execution — coding work delegates to interchangeable backends (Claude Code first) behind a small adapter port.
Architecture at a glance
- Python 3.11+, single package — no Docker, no service stack.
- PostgreSQL-only core (embedded server via the
embedded-pgextra): the work queue, event log, artifact graph, blobs, and full-text search all live in one database. - Four kernel subsystems: Artifact Engine, Workflow Engine, Skill Engine, Execution Port. Everything else is a plugin behind an entry point.
Full design documents live in the repository: github.com/vinit-devops/flow-speckit.
License
Apache-2.0.
Metadata
Release files for flow-speckit 0.1.0.post1
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| flow_speckit-0.1.0.post1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 42.8 kB
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