Works with the AI tools you already use
FPGA 12/13 · Deploy Claude — Release and Handover
Packages validated FPGA designs into deployment-ready releases for users without hardware backgrounds.
Secure checkout via Stripe
See it in action
You say
Prepare a release package for the validated FFT accelerator. The software team needs to run it on the target board without touching HDL or pragmas.
Your agent does
Release package prepared.
- Bitstream: fft_v2_res_4k.bit (sourced from repo)
- API: Call signature identical to fft_ref.py
- Test: acceptance_test.py included (Software vs HW check)
- Handover: Gain identified as 12x end-to-end (repartitioning based). Manual loading fallback documented.
What you get
About this skill
The problem
FPGA accelerators often fail at the handoff stage because domain users without hardware backgrounds cannot navigate HDL, constraints, or complex synthesis tools. A technically perfect design is useless if the recipient cannot commission it without touching hardware-specific code.
What it does
- Packages verified bitstreams from existing repositories to avoid redundant and error-prone re-synthesis.
- Enforces call compatibility between software references and hardware variants so calling code remains unchanged.
- Generates automated receiver acceptance tests to verify bit-level results against software references within defined tolerances.
- Produces a transparent handover document that distinguishes between raw kernel speedups and actual end-to-end performance gains.
- Builds release manifests with checksums to ensure every delivery artifact is traceable to its original source state.
Why this beats prompting it yourself
This skill enforces a rigid delivery protocol that prevents common deployment traps like "hidden HDL" requirements or missing manual fallbacks. It ensures the agent focuses on the recipient's ability to run the system without hardware knowledge, rather than just generating files.
Use cases
- Creating a ready-to-run FPGA release package for a software engineering team.
- Generating a handover document that honestly communicates performance gains and limitations.
- Setting up a two-stage deployment path to validate designs on cheap hardware before target rollout.
- Standardizing an API signature to allow seamless switching between CPU and FPGA implementations.
Known limitations
Requires a fully worked-through release catalog from preceding documentation stages to begin the packaging process.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
Reviews
No reviews yet
Be one of the first to try it. Every listed skill passes our trust checks below.
Security scanned
Passed our 8-point scan before listing
Fresh listing
Recently published to Agensi
30-day refund
Not a fit? Get your money back
Trust & safety
Security scanned
Verified clean today
- One-time purchase, yours forever