Agent-readable docs index: /llms.txt. Full docs in one file: /llms-full.txt. Download /docs.zip to grep all markdown files locally.

watchman

The Watchman skill keeps inference work evidence-first. It distinguishes a read-only hardware snapshot from an active canary, a bounded saturation experiment, a local artifact inspection, and a capacity estimate.

Install the skill and binary

The registry distributes Watchman as watchman. Install the checksum- verified binary through the hosted path, then add the agent skill through the Skills CLI.
curl -fsSL https://tools.yshubham.com/watchman/install.sh | sh npx skills add bas3line/rool-repo --skill watchman --agent '*' --global --yes
Keep the tool local to the evidence source. Run it where the GPUs, process table, endpoint reachability, and secret-file paths are actually available; do not turn a support report into a remote credential collection channel.

Select the right workflow

Begin with read-only evidence. Use snapshot, ps, top, or doctor to understand hardware and telemetry coverage. Invoke canary only when a real synthetic generation request is appropriate; invoke benchmark saturation only when intentionally measuring an explicit fixed-concurrency ladder.
Capacity is a model, not live allocation telemetry. Use it to state a topology and conservative bounds, then retain its caveats in the rollout record. Read health and collection and inference and capacity before choosing a command.

Preserve the decision trail

Save the report that justified the deployment choice. Offline benchmark and canary comparison use complete, compatible reports; missing or incompatible evidence remains not-evaluable instead of turning into a green gate.
For service deployment, history rotation, remote-listen safety, and rollback thinking, use the Watchman rollout guide.
Do not use direct secrets or customer prompts in CLI flags. Prefer secret files and non-secret workload identities so process listings and report output do not become an accidental disclosure channel.