What problem does it solve?
Keeping the OpenClaw and Hermes comparison columns of the ZeroClaw feature matrix accurate requires manually auditing two large external repositories, and guessing from directory names or memory produces wrong parity verdicts that mislead readers.
Core Features & Use Cases
- Source-walked parity verdicts: Shallow-clone both competitor repos, resolve provider/channel/tool aliases, and verify each matched module is actually wired and called before marking a cell supported, partial, planned, or none.
- Issue-tracker planned detection: Search open feature requests via the GitHub CLI so slots with no module but an open request are marked planned instead of none.
- Guarded TOML updates: Write docs/book/feature-matrix-parity.toml with pinned clone SHAs and checked dates, then validate with the cargo feature_matrix guard test and regenerate the rendered mdbook page.
- Use Case: When the rendered feature matrix shows Unknown cells for OpenClaw or Hermes, run this workflow to re-walk both trees, fill the parity TOML with auditable verdicts, and confirm the live page renders correctly.
Quick Start
Update the feature matrix by re-walking the OpenClaw and Hermes repositories and filling the parity TOML with verified support statuses.
