veripower
Manifest valid★ 6An open-source agent flow from natural language spec through Verilog RTL and UVM verification to front-end signoff on commercial EDA tools
An open-source agent flow for front-end chip design
VeriPower is an open-source agent flow that takes a natural-language spec all the way to front-end signoff on commercial EDA tools. A deterministic engine sits underneath, recording every action in an append-only log. All pipeline status is derived from that log on demand, never stored as a flag or snapshot. The agent can iterate on its own, but every LLM-authored oracle needs a human sign-off.
Ships as a plugin for Claude Code, opencode, DeepSeek Harness, and Codex.
How it works
A deterministic engine owns the facts. Agents and humans are proposers. The engine keeps an append-only record of every action and conclusion, and whether a stage is done, stale, or failed gets computed from that record each time you ask. An orchestrator queries the engine for one action, carries it out, queries again. No state carried between queries.
Every verification conclusion is fingerprinted against the content it consumed and produced. Edit something upstream and the downstream conclusions go invalid on the next query. Design and verification both start from the spec but then diverge, so the reference model is derived from the spec, not from the implementation. EDA tool verdicts are authoritative. LLM-authored oracles are good enough for iteration but need human endorsement for signoff, and that endorsement lapses if the oracle content changes.
More in ARCHITECTURE.md (中文).
Pipeline
Eight stages, spec through power analysis. The dependency graph falls out of each rule's artifact declarations.
Reference implementation wraps Synopsys tools (SpyGlass, Design Compiler, PrimeTime, VCS+UVM). Each stage is a self-contained skill, so you can swap one (Verilator for simulation, Yosys for synthesis) without touching the rest.
Results
Three front-end design tasks, bare Claude Code vs. Claude Code + VeriPower. Same LLM, same spec, same EDA tools.
| Benchmark | Scale | Baseline | + VeriPower | |---|---|---|---| | gateGPT — fixed-point GPT inference | 346K gates | 3 of 4 coverage metrics below 90% | pass | | FSA — FlashAttention accelerator | 32K gates | 2 unresolved CDC violations | pass | | Coral-NPU — RISC-V ML accelerator | 3.4M gates | 6/19 tests | 19/19 |
Across these tasks, VeriPower closes verification gaps in coverage, CDC and test execution.
Quickstart
Claude Code
claude plugin marketplace add chipweaver/veripower
claude plugin install veripower@chipweaver
Or point at a working copy: claude --plugin-dir /path/to/veripower.
opencode
Add the plugin to ~/.config/opencode/opencode.json, or to a project-level
opencode.json:
{ "plugin": ["veripower@git+https://github.com/chipweaver/veripower.git"] }
Stage dispatch runs subagents in the background, which opencode gates behind an environment variable, so start it with:
OPENCODE_EXPERIMENTAL_BACKGROUND_SUBAGENTS=true \
OPENCODE_EXPERIMENTAL_OUTPUT_TOKEN_MAX=131072 opencode
opencode 1.18.30 has a default 32,000-token completion ceiling. For models that support
longer output, set the second flag to the model's declared output limit; 131072 is
an example.
DeepSeek Harness
Install into the profile you run:
dsh plugin --profile web add "veripower@git+https://github.com/chipweaver/veripower.git"
Run the web profile (dsh web), not the one-shot headless profile.
Codex
Native plugin and subagents (tested with CLI 0.153.4 on Linux):
codex plugin marketplace add chipweaver/veripower
codex plugin add veripower@chipweaver --json
Use the returned installedPath to run python3 <installedPath>/codex/setup.py,
then launch codex --profile veripower. Review the two VeriPower hooks in /hooks
and start a new session. Setup adds native command approval rules and a profile
that routes oracle judgments to the human reviewer. See Codex setup and runtime
behavior for upgrades, background jobs and verification scope.
Ask it to list its skills — the twelve VeriPower ones confirm the install.
Run the brainstorm skill to settle requirements first, then tell the agent:
Run the design flow for {module_dir}
Full walkthrough in the user manual (中文).
Requirements. Python 3.10+, jsonschema >= 4.18, referencing, PyYAML. Synopsys EDA tools, swappable per skill.
Citation
Paper forthcoming.
Version: v0.2.4. MIT License. Contributing. Issues.
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