Personal Agent Benchmark Pack for QA Scenario Testing

A compact QA scenario pack for local personal assistant workflows, using existing private QA stacks and synthetic channels. Ideal for developers verifying reminder, thread, and memory preference features.

Read this when

  • Running local personal agent reliability checks
  • Extending the repo-backed QA scenario catalog
  • Verifying reminder, reply, memory, redaction, safe tool followthrough, task status, share-safe diagnostics, proof-backed completion claims, and failure recovery

The Personal Agent Benchmark Pack is a compact, repository-backed QA scenario pack designed for local personal assistant workflows. This is not a general-purpose model benchmark, and it does not require a separate runner. Instead, it relies on the existing private QA stack (QA overview), the synthetic QA channel, and the current qa/scenarios YAML catalog.

Scenarios

Ten scenarios are defined in qa/scenarios/personal/*.yaml:

Scenario idChecks
personal-reminder-roundtripFake personal reminders through local cron delivery
personal-channel-thread-replyFake DM and thread reply routing through qa-channel
personal-memory-preference-recallFake preference recall from the temporary QA workspace memory files
personal-redaction-no-secret-leakFake secret no-echo checks
personal-tool-safety-followthroughSafe read-backed tool followthrough after a short approval-style turn
personal-approval-denial-stopApproval denial stop behavior for a sensitive local read request
personal-task-followthrough-statusProof-backed task status reporting that keeps pending, blocked, and done separate
personal-share-safe-diagnostics-artifactShare-safe diagnostics artifacts that keep useful status while omitting raw personal content
personal-no-fake-progressProof-backed completion claims that avoid fake progress before local evidence exists
personal-failure-recoveryFailure recovery that reports partial status and keeps retry boundaries clear

The machine-readable personal-agent profile is located in the root taxonomy.yaml as semantic coverage IDs. Every primary owner is resolved by QA Lab directly from the catalog, so there is no secondary scenario-ID list. To execute it, use:

OPENCLAW_ENABLE_PRIVATE_QA_CLI=1 pnpm openclaw qa run \
  --qa-profile personal-agent \
  --provider-mode mock-openai \
  --concurrency 1

Repeat the --scenario flags to narrow the profile. Neither the scenario file order nor the taxonomy order influences membership or the sequence of execution.

The pack is aimed at qa-channel with mock-openai or another local QA provider lane. Avoid pointing it at live chat services or real personal accounts.

Privacy Model

Scenarios exclusively employ fake users, fake preferences, fake secrets, and the temporary QA gateway workspace that the suite creates. They must never read or write actual OpenClaw user memory, sessions, credentials, launch agents, global configs, or live gateway state.

Artifacts remain within the existing QA suite artifact directory and are handled like test output. Redaction checks rely on fake markers, so any failures are safe to inspect and file in issues.

Extending the pack

Add new .yaml cases under qa/scenarios/personal/, declare the exact primary coverage ID they demonstrate, and include that semantic ID in the taxonomy profile when it fits this benchmark. Keep each case small, local, deterministic in mock-openai, and focused on a single personal assistant behavior.

Suitable follow-up candidates: redacted trajectory export checks, local-only plugin workflow checks.

Do not introduce a new runner, plugin, dependency, live transport, or model judge until the scenario catalog contains enough stable cases to justify such a surface.

467 words · updated Jul 31, 2026