hushh-labs

puppy-one-harness

Use when running, grading, or extending the on-device model harness for Puppy One, including the review-queue judge handoff, capability probing, and the evolution ledger.

hushh-labs 40 87 Updated 1w ago

Resources

2
GitHub

Install

npx skillscat add hushh-labs/hushh-research/puppy-one-harness

Install via the SkillsCat registry.

SKILL.md

Puppy One Harness Skill

Purpose and Trigger

  • Primary scope: puppy-one-harness
  • Trigger on benchmarking a local model, grading its output, adding a model to
    the ladder, or reading the evolution ledger.
  • Avoid overlap with quality-contracts and backend-agents-operons.

The harness answers two different questions and must never conflate them. The
benchmark asks well-formed and fast; the judge asks correct. A model can emit
a perfectly shaped save_to_pkm call that files a dietary restriction under
finance.accounts, and the shape check passes it.

Coverage and Ownership

  • Role: spoke
  • Owner family: backend

Owned repo surfaces:

  1. .codex/agents/local_model_judge.toml
  2. .codex/skills/puppy-one-harness/references/judging-contract.md

Non-owned surfaces:

  1. consent-protocol
  2. hushh-webapp
  3. backend

Do Use

  1. Running the benchmark or the judge over a local model.
  2. Grading a review queue, or reviewing someone else's verdicts.
  3. Adding a model to the ladder, or reading the ledger for a trend.
  4. Grading the device's real daily jobs (the cron quality suite, see
    .codex/skills/puppy-one-harness/references/cron-quality-suite.md).

Do Not Use

  1. Changing the PKM write path or the vault (security-audit).
  2. Provider routing or the on-device gate itself (backend-runtime-governance).
  3. Frontend surfaces for Puppy One (frontend-surface-placement).

Read First

  1. .codex/skills/puppy-one-harness/references/judging-contract.md
  2. .codex/agents/local_model_judge.toml

Workflow

  1. Collect outputs from the local model, then write a review queue. Controls are
    planted, shuffled per run, and unmarked; their answers live in the manifest.
  2. Grade in a session that did not write the queue. This cannot be enforced
    from a script, so it is a discipline the report states rather than assumes.
  3. Never open run-manifest.json while grading. It holds the control positions,
    and reading it destroys the only property that makes a pass meaningful.
  4. Every wrong verdict cites the offending value verbatim. Ingest checks the
    citation against the output and discards it if absent, because an uncited
    failure is indistinguishable from a hallucinated one.
  5. Grade every row. Ungraded rows void the run: skipping the hard ones would
    raise accuracy for free.
  6. Ingest, then append to the ledger. Record void runs too — dropping them makes
    the ledger an unbroken record of successes.
  7. Before comparing two runs, check the capability profile. A model tested via
    tool calling and one tested via JSON mode were not asked the same question.

Handoff Rules

  1. If the request is still broad or ambiguous, route it back to backend.
  2. If the finding is a provider-routing or gate issue, use
    backend-runtime-governance.
  3. If it touches the vault or the PKM write path, use security-audit.

Required Checks

python3 .codex/skills/agent-orchestration-governance/scripts/agent_orchestration_check.py
python3 .codex/skills/codex-skill-authoring/scripts/skill_lint.py

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