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The Personal Agent Benchmark Pack is a small repo-backed QA scenario pack for local personal assistant workflows. It is not a generic model benchmark and needs no new runner: it reuses the private QA stack (QA overview), the synthetic QA channel, and the existing qa/scenarios YAML catalog.

Scenarios

Ten scenarios, defined in qa/scenarios/personal/*.yaml: The machine-readable personal-agent profile lives in root taxonomy.yaml as semantic coverage IDs. QA Lab resolves every primary owner from the catalog; there is no second scenario-ID list. Run it with:
Use repeated --scenario flags to narrow the profile. Scenario file and taxonomy order do not affect membership or execution order. The pack targets qa-channel with mock-openai or another local QA provider lane. Do not point it at live chat services or real personal accounts.

Privacy Model

Scenarios use only fake users, fake preferences, fake secrets, and the temporary QA gateway workspace created by the suite. They must not read or write real OpenClaw user memory, sessions, credentials, launch agents, global configs, or live gateway state. Artifacts stay under the existing QA suite artifact directory and are treated like test output. Redaction checks use fake markers so 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 prove, and add that semantic ID to the taxonomy profile when it belongs in this benchmark. Keep each case small, local, deterministic in mock-openai, and focused on one personal assistant behavior. Good follow-up candidates: redacted trajectory export checks, local-only plugin workflow checks. Avoid adding a new runner, plugin, dependency, live transport, or model judge until the scenario catalog has enough stable cases to justify that surface.