keysight-meters-cli-orchestration

name

keysight-meters-cli-orchestration

description

Use when modifying, testing, reviewing, or orchestrating Keysight_Meters_Logger Meters CLI/worker subprocess workflows, including start-trigger-record, JSON/JSONL contracts, dry-run, simulate, wait-ready, status, send-command, stop, POST /command, GET /status, report.json, CSV, run_id correlation, and live resource safety. Do not use for CSS-only UI styling, general documentation polishing, or unrelated Python refactors.

Keysight Meters CLI Orchestration

This skill helps Codex follow the public Keysight_Meters_Logger Meters CLI/worker subprocess contracts. It is an instruction-only skill. It does not provide an instrument driver, replace the CLI, or authorize live hardware work.

Contract lookup order

Before making contract-sensitive decisions, read the relevant contracts in this order:

1. If working inside the Keysight_Meters_Logger repository and docs/contracts/ is available, treat those files as the upstream source of truth.
2. If this skill is installed standalone and has a local references/ directory, read the copied contract files there as a contract snapshot.
3. If both docs/contracts/ and references/ are available and appear to differ, warn the user before making contract-sensitive changes.

In executable-only workspaces, such as a folder with keysight-logger*.exe but no repository docs/contracts/, first check this skill package's references/ directory. Read all six contract snapshots before using CLI help. If they are not readable, stop and report a missing-contract blocker. CLI help may confirm installed behavior only after contract lookup has been attempted.

Relevant contracts:

• common-worker-protocol.md
• common-cli-jsonl-contract.md
• common-orchestrator-workflows.md
• meters-worker-contract.md
• meters-cli-jsonl-contract.md
• meters-orchestrator-workflows.md

Non-negotiables

• Treat machine JSON, JSONL, structured artifacts, CSV, report.json, and process exit codes as the evidence surface. Human text is diagnostic only.
• Parse CSV with a CSV parser. Meters CSV fields can contain quoted JSON metadata; comma splitting is not valid evidence.
• For acquisition changes, validate in this order: dry-run JSONL, simulator JSONL with a finite bound such as --max-samples, then live only with an explicit user-selected --resource.
• Keep dry-run and simulator validation as separate start-trigger-record invocations. Never combine --dry-run and --simulate.
• Do not scan, guess, rotate, brute-force, or silently substitute live VISA resource strings inside an acquisition workflow.
• Treat executable forms as equivalent only when they preserve the documented CLI/worker subprocess behavior. Direct in-process Python calls are outside this contract unless a separate Python API contract defines them.
• Wait for ready JSONL or wait-ready --json before lifecycle requests. Treat readiness as control-plane availability, not measurement completion.
• Do not use existing run-artifacts as evidence for a requested fresh validation. Dry-run JSON, worker JSONL, client JSON, CSV, summary, run_id, and exit code must come from the same fresh runtime session.
• Do not stop, kill, or reuse unrelated pre-existing keysight-logger processes unless the user explicitly approves it. Use a fresh explicit port for the owned worker, or report a pre-existing-worker/port blocker.

Executable orchestration rules

Apply these rules before running or preparing executable Meters workflows such as start-trigger-record, wait-ready, status, send-command, or stop:

• Read common-orchestrator-workflows.md and meters-orchestrator-workflows.md before choosing CLI flags, simulator resource strings, process-launch patterns, or software-trigger sequencing.
• Use the CLI spellings and simulator resource strings shown in the contracts as the source of truth. Do not invent flags such as --function or --trigger-source, SCPI-form measurement values such as CURR:DC, or simulator aliases such as SIMULATOR unless the repository contracts or CLI help explicitly support them.
• Every non-dry-run worker invocation must use owned-process cleanup: keep the worker process handle, collect stdout JSONL and stderr, request stop --json if the owned worker is still running, wait a bounded time for process exit, and report the worker exit code. If the exit code is not collected, report incomplete lifecycle convergence.
• In executable-only Windows workspaces, an explicit high --sw-trigger-port plus wait-ready --json is an acceptable readiness synchronization path when the worker subprocess remains observable and its stdout JSONL, stderr, artifacts, and exit code are collected.
• In executable-only Windows workspaces where Python launchers are unavailable, Node.js child_process.spawn is an acceptable fallback for orchestration if it keeps the owned worker handle, streams stdout/stderr, captures client JSON, performs cooperative cleanup, and reports the worker exit code.
• For software-trigger workflows, treat start-trigger-record as a worker subprocess. Stream stdout JSONL incrementally until ready, send the documented software_trigger, continue through expected sample and summary, then check artifacts and exit code.
• If stdout ready is not observed within a bounded startup window but the worker subprocess is still owned and observable, use wait-ready --json as a control-plane readiness fallback. Continue collecting stdout JSONL through process exit, and require the final artifacts to show the same run_id across stdout JSONL, wait-ready, status, sample, and summary.
• Do not treat a host-side wrapper timeout as worker failure until stdout JSONL events, process state, stderr, client command results, status endpoint state when available, and generated artifacts have been checked. Report the last observed JSONL event, whether ready was observed, whether software_trigger was sent, and whether summary was reached.
• On Windows, do not use WaitForExit, host-side process waits, or wrapper command timeouts as the first synchronization point for software-trigger workflows. Start the worker subprocess first, read stdout JSONL immediately, then use ready, optional wait-ready --json, status --json, and exactly one send-command --json as distinct synchronization steps.
• Treat summary as acquisition completion evidence, not proof that the worker process has already exited. Treat status.captured as runtime state evidence, not proof that worker cleanup is complete.
• Treat stop --json responses such as already_stopped as normal cleanup states unless combined with other failure evidence.
• Prefer Python subprocess.Popen or the repository-documented orchestrator pattern for software-trigger worker orchestration so stdout JSONL, run_id, process exit code, and cleanup remain observable.
• For repeated executable-only simulator smoke validation, prefer the bundled helper scripts/run_meter_sim_workflow.mjs when Node.js is available. It runs a dry-run and an independent simulator software-trigger workflow, writes JSONL/CSV/report artifacts, and exits non-zero if the evidence contract is not satisfied.
• Do not use detached shell-specific launch mechanisms such as PowerShell Start-Process or cmd /c start /B unless the repository explicitly documents that pattern. Detached shell launch can hide stdout JSONL, exit codes, cleanup state, and run_id correlation. Diagnostic one-off use of Start-Process is not final workflow evidence.
• If a required CLI spelling, resource string, or launch pattern is unclear, stop and re-read the source-of-truth contracts before running. Do not probe by inventing flags and treating CLI rejection as the normal discovery path.

Work pattern

1. Identify whether the task touches the CLI/worker contract surface.
2. Read the relevant source-of-truth contracts before editing or reviewing.
3. Keep proposed changes inside the documented lifecycle and safety boundaries.
4. Prefer no-hardware validation first: dry-run, simulator, and contract tests.
5. Require explicit user-selected resources before proposing live runs.
6. Report any contract impact, validation coverage, and remaining live-hardware risk explicitly.

Bundled simulator helper

Use scripts/run_meter_sim_workflow.mjs only for no-hardware simulator smoke validation. It does not authorize live resources or VISA discovery.

Typical executable-only use:

node .agents\skills\keysight-meters-cli-orchestration\scripts\run_meter_sim_workflow.mjs `
  --exe .\keysight-logger-1.5.0.exe `
  --out .tmp_tests\meter_sim_software_trigger `
  --resource SIM::34461A `
  --measurement current-dc `
  --max-samples 1 `
  --port 18765

The helper writes:

• dry_run.jsonl
• sim_worker_stdout.jsonl
• sim_worker_stderr.txt
• sim_samples.csv
• sim_report.json

Treat the helper exit code as a verification result. A successful run requires dry-run safety fields, exactly one accepted software trigger, matching run_id values across worker JSONL/client responses/artifacts, one CSV row, summary.ok: true, expected captured count, zero errors, and worker exit code 0.