Agent Skills: Product Design Harness

Product Design Harness

Decide whether a product direction should continue, be verified, or be reframed anywhere in the product loop.

Execution includes design, implementation, prototype, launch, growth, automation, or investment.

Start

Load in this order:

1. resources/schemas/session-config.schema.json: set working_language; keep canonical_identifiers in English.
2. resources/knowledge/ontology.json: use the canonical UX3 knowledge kernel and its approved Flow definitions.
3. resources/knowledge/rules.json: load required rules plus only triggered conditional rules.
4. resources/prompts/start-review.md.

Then fill resources/templates/product-brief.md, select the smallest responsible mode, and return resources/schemas/review-result.schema.json.

Validate every review result with resources/scripts/check_review.py. JSON Schema checks shape and conditional fields; check_review.py is the canonical validator for the worst-verdict, weakest-flow, and headline-tier semantic checks.

Modes

| Mode | Use when | |---|---| | Quick Gate | Small, reversible, low-risk change. | | Standard Gate | New feature, workflow, or experiment. | | UX3 Council | High uncertainty, external evidence, meaningful risk, multiple reviewers, or human-owned trade-off. |

Handoff is not a review mode. When a prior review already returned continue, reuse its context pack instead of running a new review.

Reversibility lowers mode, not the review requirement.

UX3

Review three connected dimensions:

| Flow | Core question | |---|---| | User Flow | Who is the product for, who is affected, what are they trying to accomplish, and what cost or loss of control exists now? | | Evidence Flow | What signal was observed, where did it come from, what interpretation is being made, what counter-signal weakens it, and what decision impact follows? | | Business Flow | Who creates value, receives value, pays or decides, bears cost or risk, and can the exchange remain viable and legitimate? |

Then inspect the intersections: Situated Understanding, Viable Learning, and Sustainable Value Exchange.

UX3 Decision Kernel

Apply the same reduction sequence to every submitted review:

1. Validate lane contracts and evidence references with resources/scripts/check_review.py.
2. Reduce to the worst verdict and deterministic weakest flow.
3. Gate uncertainty, risk, reversibility, and human-owned calls.
4. Emit one canonical verdict, next action, execution boundary, and stop conditions.

Do not average lanes. Human-owned calls are recorded through an accountable decision record; they are not converted into a machine score.

Before handoff, name product organization, issuer, stakeholder effects, and accountable owner. Missing issuer or owner blocks implementation.

Operating Rules

• Do not implement during review.
• verify branch: verify authorizes only the exact proof_step and never general coding.
• continue branch: continue plus a valid context pack authorizes implementation.
• Every result states may_do, must_not_do, and must_ask.
• List disconfirming evidence before support.
• Do not average reviewer verdicts.
• The weakest flow controls the next action.
• External tools return evidence receipts, not verdicts.
• Evidence tier controls action size; confidence does not upgrade weak proof.
• Council mode requires independent reviews and a challenge round.
• If all independent Council reviews return continue, a valid resources/schemas/red-team-review.schema.json result must be attached to the Council input before synthesis.
• Designer taste is a human-owned input, never an evidence score.
• Incoming feedback must be classified before it changes direction or work.
• Human-owned decisions stay human-owned.

Triggered Distilled Rules

Load only rules whose observable trigger applies. These families refine the three Flow reviews; they do not create new verdicts or allow a strong Flow to outvote a weak one.

| Situation | Required rule | |---|---| | Mental-model mismatch, hidden capability, or misunderstood consequence | ux3.rule.mental_model_alignment | | Cognitive or recovery burden across human, task, tool, and environment | ux3.rule.human_factors_load | | Research claim, synthetic user, simulation, interview, survey, test, or analytics result | ux3.rule.research_validity | | Value proposition, positioning, buyer, channel, or GTM path before fit is proven | ux3.rule.value_market_path | | Agent plan or tool action that needs visibility, control, handoff, or recovery | ux3.rule.human_agent_interaction | | Retention, personalization, or gamification that changes repeated behavior | ux3.rule.motivation_ethics |

Outcome

| Verdict | Required next step | |---|---| | continue | Create resources/templates/context-pack.md within the execution boundary. | | verify | Run one proof step only. | | stop_reframe | Stop execution and return a better product question. |

Use triggered rule IDs for detail instead of duplicating every rule in prompts. Common triggers include ux3.rule.actor_boundary, ux3.rule.problem_hypothesis, ux3.rule.evidence_separation, ux3.rule.minimum_validated_proof, ux3.rule.feedback_classification, and ux3.rule.human_judgment. The distilled trigger table above covers additional rules that activate only when their specific product condition appears.

Use resources/docs/HARNESS.md for the handbook, resources/docs/OPERATING-PROTOCOL.md for the six-gate protocol, resources/docs/CONTRACTS.md for output rules, and resources/examples/ for worked reviews.