Openshard

OpenShard

Receipts for AI coding agents.

AI coding agents can write code, but developers still need a clear record of what happened: what ran, what changed, what checks passed or failed, what it cost, and whether the saved record still matches its fingerprint.

OpenShard gives AI coding work a local receipt. It starts with receipts and grows into the control layer for AI coding workflows.

Agents write code. OpenShard keeps the receipt.

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Why OpenShard exists

AI coding agents are becoming good enough to work on real repos, infrastructure, and production-shaped systems.

That creates a new problem. Not “can the model write code?” but:

• Which model or workflow handled the task?
• What files did it inspect or touch?
• What did it change?
• Did checks pass, fail, skip, or not run?
• What did the run cost?
• Was anything risky blocked or reviewed?
• Is there a durable receipt of what happened?

OpenShard is built for the work around the agent: routing, checks, risk gates, cost awareness, feedback, local history, and Shard receipts.

The valuable unit is not a single model call. It is a completed engineering task with a record you can inspect later.

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What OpenShard does

OpenShard is a CLI tool for controlling and recording AI coding work.

It can:

• Run real repo tasks through a controlled execution path
• R