Feature Value Governance

Overview

Use this skill to decide whether a proposed feature deserves investment before it enters a roadmap or a build. It surfaces the business intent the feature serves, the revenue or operational lever it pulls, the user evidence behind it, its alignment to the opportunity tree, its complexity cost, and its risk of overreaching into compliance, accessibility, or privacy.

The skill is knowledge-aware: it declares the knowledge it needs as slot types (see skill-knowledge-dependency.yaml) and lets AletheIA's Knowledge Governance Layer resolve which packs fill them. It carries no proprietary framework, policy, or persona content of its own. It runs in two modes:

• Generic mode — no authorized pack is available. The skill applies its general criteria and marks the output mode: generic with no fabricated pack citations.
• Knowledge-aware mode — the resolver returns at least one satisfying pack. The skill reasons from the capsule first, respects active restrictions, and cites every consumed pack as pack_id@version.

When to Use

• A feature is proposed and someone must decide whether it is worth doing.
• Prioritizing or sequencing a backlog where value and cost are contested.
• A roadmap decision needs an explicit business intent and lever, not just a request.
• A feature might overreach into compliance, accessibility, or privacy and the risk needs naming before commitment.

When NOT to Use

• The decision to build is already made and only execution planning remains (use feature-planning).
• The change is tiny and local with obvious value.
• The task is operating the Knowledge Governance Layer itself — registering a source (knowledge-source-evaluation), resolving a source conflict (knowledge-conflict-resolution), or risk-checking a sensitive source before use (restricted-context-check).
• No problem framing exists yet; there is nothing whose value can be judged.

Core Moves

1. Frame the feature and resolve knowledge. State the proposed feature in one line. Identify which knowledge slots the task needs (strategic_framework always; accessibility_guidelines and operating_model by task shape). Read the resolved context pack: satisfied slots, gaps, conflicts, active restrictions. If a required slot is unsatisfied, apply fallback_behavior and say so loudly.
2. Surface business intent. Name the business or product intent the feature serves. In knowledge-aware mode, anchor it to the resolved strategic_framework; in generic mode, derive it from stated goals and mark the inference.
3. Name the lever. Identify the revenue or value lever the feature pulls (acquisition, activation, retention, expansion, efficiency, margin, strategic_defense — the canonical taxonomy shared with the Feature Value Governance Contract). One feature, one primary lever.
4. Weigh user evidence. Cite the user evidence supporting the feature from the personas slot when present; otherwise state the assumption explicitly with an assumption marker.
5. Check opportunity-tree alignment. Place the feature against the opportunity / outcome it claims to serve. Flag features that serve no live opportunity.
6. Estimate complexity cost. Give a coarse complexity read (low / medium / high) and the main drivers. Complexity is a cost against value, not a veto on its own.
7. Assess overreach risk. Judge whether the feature reaches into compliance, accessibility, or privacy. When required_when triggers match (interface change, content decision, customer-facing experience), the accessibility_guidelines slot becomes required; an unmet required slot stops the analysis per fallback.
8. Render the verdict and audit trail. Produce the Expected Output block: a worth-doing verdict with rationale, every consumed pack cited as pack_id@version, unsatisfied slots with the fallback applied, and any conflicts resolved via the source precedence policy.

Optional Modules

• Revenue lever detail — When the value claim is contested, delegate to the revenue-lever-mapping skill for a driver model (which funnel step, which cost line) instead of reasoning inline.
• Opportunity-tree mapping — When the backlog has competing bets, delegate to opportunity-tree-alignment to draw the outcome → opportunity → lever → feature path and flag orphans.
• Complexity audit — When complexity is the deciding factor, delegate to feature-complexity-audit for the four-dimension permanent-cost scorecard and reduction recommendation.
• Sunset hook — When the subject is an existing feature (keep / limit / refactor / deprecate / remove) rather than a new bet, hand off to sunset-decision and record the result as a sunset decision on the contract.
• Overreach deep-check — When an accessibility_guidelines, privacy, or compliance dimension is in play, run the dimension against the resolved normative pack (or, in generic mode, against general norms with a clear generic marker).
• Persona evidence pull — When personas resolves, pull the relevant capsule excerpt (respecting retrieval mode) instead of paraphrasing the whole source.
• Conflict resolution hook — When two packs disagree on a decision-relevant point, hand off to knowledge-conflict-resolution or apply the precedence policy inline and record it.

Activation Triggers

• Always: declare and attempt to resolve strategic_framework; run generic mode loudly if unsatisfied and the fallback permits.
• Use the overreach deep-check and treat accessibility_guidelines as required when the task is an interface_change, content_decision, or customer_facing_experience.
• Treat operating_model as required when the task is a roadmap_decision or prioritization_decision.
• Pull persona evidence when the personas slot resolves; otherwise mark the user-evidence claim as an assumption.
• Delegate to feature-complexity-audit when complexity is the pivotal factor in the verdict.
• Hand off to sunset-decision when the subject is an existing feature rather than a new bet.
• Invoke the conflict resolution hook when resolved packs disagree.
• Record the verdict against the AletheIA Feature Value Governance Contract and apply the seven readiness gates; see the product-value-governance domain pack.

Expected Output

feature_value_analysis:
  feature: <one-line description>
  mode: generic | knowledge_aware
  business_intent: <intent served; cite framework pack in knowledge-aware mode>
  lever:
    primary: acquisition | activation | retention | expansion | efficiency | margin | strategic_defense
    rationale: <short>
  user_evidence:
    summary: <what the evidence says, or the assumption made>
    is_assumption: <bool>
  opportunity_alignment:
    serves: <opportunity / outcome, or "none">
    aligned: <bool>
  complexity:
    cost: low | medium | high
    drivers: [<...>]
  overreach_risk:
    compliance: none | possible | likely
    accessibility: none | possible | likely
    privacy: none | possible | likely
    notes: <short>
  verdict:
    worth_doing: yes | no | conditional
    conditions: [<...>]            # when conditional
    rationale: <short>
  knowledge_used:
    - slot: <slot-name>
      pack: <pack_id@version>
      retrieved_scope: capsule | excerpt | metadata | full
      restrictions: [<...>]
  unsatisfied_slots:
    - slot: <slot-name>
      fallback: <applied fallback>
  conflicts:
    - between: [<pack_id@version>, <pack_id@version>]
      prevailing: <pack_id@version>
      reason: source_precedence_policy

Verification

• Every required slot is either satisfied or stopped per fallback_behavior; no silent generic fallback on a required slot.
• The output declares mode; generic-mode output carries no fabricated pack citations.
• Each consumed pack is cited as pack_id@version; knowledge-aware output without citations is invalid.
• No verbatim text from a confidential or higher source appears in the output, logs, or handoff.
• The verdict names exactly one primary lever and ties it to a stated business intent.
• Overreach dimensions that triggered a required_when slot were actually assessed against the resolved (or generically marked) norm.
• Conflicts, if any, name the prevailing pack and the precedence reason.

Handoff Signals

• A worth_doing: yes verdict hands off to feature-planning for delivery shaping.
• An unmet required slot hands back to the requester with the exact authorization that would unlock knowledge-aware mode.
• A likely overreach risk on compliance, accessibility, or privacy routes to human review before commitment.
• Unresolved conflicts between mandatory and lower-tier sources escalate to human review; do not invent a compromise.
• Carry active restrictions forward; do not let capsule-only or no-export drop at the boundary.

Pairs Well With

• revenue-lever-mapping
• opportunity-tree-alignment
• feature-complexity-audit
• sunset-decision
• feature-planning
• knowledge-source-evaluation
• knowledge-conflict-resolution
• restricted-context-check

Anti-patterns

• Naming a specific framework, policy, or persona as a hard requirement instead of declaring a slot type.
• Inlining capsule or framework text into this skill or its templates.
• Producing a confident verdict in generic mode as if a governed source were present.
• Citing a pack in knowledge-aware mode without pack_id@version.
• Treating complexity as an automatic veto, or treating high value as license to overreach into compliance/accessibility/privacy.
• Resolving a mandatory-vs-lower-tier source conflict by splitting the difference.