ai-feature-prd-spec

name	ai-feature-prd-spec
description	Generate the AI-Feature PRD Spec: IEEE 830-form requirements for every AI-powered feature, with hallucination tolerance, latency budget, $/call ceiling, abstain criteria, citation policy, consent and training-data exclusion clauses, and acceptance tests anchored to the eval harness.
metadata	{"use_when":"Use for any feature whose behaviour is produced or modified by an LLM, vision model, embedding-based retrieval, agent, or fine-tune.","do_not_use_when":"Do not use for deterministic features that merely call into AI infrastructure as a passive consumer (e.g. logging).","required_inputs":"AI_Economic_Value_Brief.md, AI_Feature_Strategy_Doc.md, PRD.md, Multi_Tenancy_Architecture_Spec.md, pricing & packaging spec.","workflow":"Inventory AI-powered FRs, attach AI clauses to each, define acceptance gates against the eval harness, declare consent and data-use rules, write the AI_Feature_PRD_Spec.md.","quality_standards":"Every AI-powered FR shall declare: hallucination tolerance, latency budget, $/call ceiling, abstain criteria, citation policy, consent or opt-in posture, training-data exclusion. Every acceptance gate shall be a numeric threshold backed by the eval harness.","anti_patterns":"Do not approve an AI FR that is verifiable only by human judgement. Do not omit the abstain rule. Do not allow free-form output where structured output is feasible.","outputs":"AI_Feature_PRD_Spec.md.","references":"Use references/ai-feature-prd-spec-template.md and the addendum at references/ai-feature-prd-addendum.md."}

AI Feature PRD Spec Skill

Overview

Produces the AI-feature complement to the generic PRD. Every AI-powered FR carries seven mandatory clauses that the generic PRD does not collect. The acceptance gates point at the eval harness as the test oracle.

Quick Reference

Attribute	Value
Inputs	AI_Economic_Value_Brief.md, AI_Feature_Strategy_Doc.md, PRD.md, Multi_Tenancy_Architecture_Spec.md, pricing & packaging spec
Output	AI_Feature_PRD_Spec.md
Standard	IEEE 830-1998, NIST AI RMF MAP/MEASURE

Core Instructions

Step 1: Inventory AI-powered functional requirements

List every FR whose output is produced or modified by an AI component (LLM call, RAG, classifier, embedding search, agent action, fine-tune).

Step 2: Attach the seven AI clauses to each FR

For each AI-powered FR, the spec MUST capture:

Clause	Form	Example
Hallucination tolerance	factuality score threshold	factuality >= 0.92 on golden set; abstain otherwise
Latency budget	P95 target ms	P95 <= 2000 ms; timeout at 8000 ms with graceful fallback
$/call ceiling	USD or token cap	<= $0.04/call; throttle when tenant > $X/day
Abstain criteria	rule	abstain when retrieval returns < 2 relevant chunks OR confidence < 0.6
Citation policy	rule	every claim about ingested document cites the source span
Consent / opt-in	rule	feature is opt-in per workspace admin; default off for EEA tenants
Training-data exclusion	rule	tenant content is not used to train the provider model; provider's no-training endpoint used

Step 3: Define structured output requirements

Where feasible the output is structured (JSON schema, function-call payload, enum). Free-form prose is reserved for user-visible text that has a separate guard (length, style, banned-terms list).

Step 4: Define safety and content rules

State which content policy applies (no medical advice, no legal advice, no investment advice, no PII generation, no protected-class judgements). Cite the safety harness scenarios that verify each rule.

Step 5: Define human-in-the-loop / contestability

Which decisions require human approval before commitment. How a user contests an output (button, reroute, escalation). Reference EU AI Act Art. 14 obligations where the feature is high-risk.

Step 6: Define rollout posture per FR

Initial rollout (canary cohort, opt-in beta, free-tier first), promotion gates (eval pass, red-team pass, hallucination SLO met for N days), and the rollback trigger.

Step 7: Define acceptance tests against the eval harness

Every AI FR has a row in the eval harness golden set with a pass threshold. Acceptance = "harness green for 30 d on this case set + red-team pass for the corresponding adversarial set".

Step 8: Write the spec

AI_Feature_PRD_Spec.md sections: 1) AI FR Inventory, 2) Per-FR AI Clauses, 3) Structured Output Requirements, 4) Safety & Content Rules, 5) Human-in-the-Loop & Contestability, 6) Rollout Posture, 7) Eval Acceptance Gates, 8) Traceability to PRD and to eval harness IDs.

Standards

• IEEE 830-1998
• NIST AI RMF MAP / MEASURE
• EU AI Act Art. 13 (transparency), Art. 14 (human oversight)
• OWASP LLM Top 10

Resources

• logic.prompt, README.md, references/ai-feature-prd-spec-template.md, references/ai-feature-prd-addendum.md.