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FPGA 08/13 · Bitstream Claude — Artifact and Custody
Converts FPGA implementations into traceable artifacts with SHA-256 manifests and bundled implementation reports.
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See it in action
You say
Generate a traceable bitstream package for the current timing-clean implementation on the Kintex-7 target. It needs to be a full configuration for the SPI flash.
Your agent does
Generating bitstream... Checksum: sha256:e3b0c442... Manifest created: project_v1.0_k7_full.json Reports bundled: timing_summary.rpt, utilization.rpt, power.rpt Archive ready for station 09 (flash). Artifact is bound to commit 8f2d9a1.
What you get
About this skill
The problem
FPGA bitstreams generated via GUI clicks lack inherent links to their source code, constraints, or timing status. This creates a traceability gap where board-level failures cannot be reliably mapped back to a specific git commit or implementation run.
What it does
- Generates configuration bitstreams as a logged script step rather than a manual GUI action.
- Computes SHA-256 checksums to bind the .bit file to its manifest and preventing artifact corruption.
- Produces a human-readable manifest containing the commit hash, tool version, and target device details.
- Bundles timing, utilization, and power reports with the bitstream to ensure implementation data stays unified.
- Differentiates between full and partial configurations in both filenames and metadata to prevent deployment errors.
Frameworks & tools
FPGA vendor tools including Xilinx Vivado and Intel Quartus. Compatible with JTAG and SPI flash programming workflows.
Why this beats prompting it yourself
Standard LLM prompts often treat bitstreams as simple files, overlooking the critical relationship between timing closure and artifact generation. This skill enforces strict "iron rules" that prevent artifact creation from failing timing runs and automates the tedious manifest creation that developers usually skip under pressure.
Use cases
- Ensuring every bitstream running in a lab can be traced to a specific Git commit.
- Automating the archival of implementation reports alongside the binary for audit trails.
- Generating distinct artifacts for both volatile RAM loading and persistent flash memory.
- Verifying artifact integrity across distributed teams using SHA-256 manifests.
Known limitations
Does not perform bit-level interpretation or reverse engineering of vendor-proprietary bitstream formats. Requires timing sign-off data from preceding implementation stages.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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