Ln 11 Opportunity Evaluator

Opportunity Evaluator

Goal: Evaluate product opportunities before implementation commitment. Start from observable demand and a reachable acquisition path, eliminate weak candidates early, and recommend one low-cost validation step without manufacturing market precision.

Execution contract: The checklist defines completion. Track each item internally as PENDING, PROVEN with evidence, CLEARED with evidence its condition is absent, or UNPROVEN with a gap; reading, delegation, tool failure, a zero exit status, or a self-reported success is not proof; only the observed outcome is. Reconcile after each section. Before returning, resolve all PENDING, count only PROVEN and CLEARED, and apply verdict and approval rules to every gap. Preserve intent, scope, and existing authorization. Continue authorized work; ask only for consequential unresolved choices or required external approval. When no one can answer during the run, state the exact question and apply the skill's verdict for the remaining gap instead of waiting or guessing. Scale depth to material risk without skipping checks. Preserve dependency and safety order; otherwise choose an appropriate verification method. Accept equivalent user or repository evidence; no other skill, named artifact, or complete lifecycle is required. Preserve source requirement and decision IDs. Bind reused evidence to relevant source versions, dirty changes, configuration, and environment; invalidate only affected claims. On continuation, reconcile task, authorization, current state, and unresolved evidence. For long work, return a compact continuation record or update an already authorized artifact; read-only skills do not persist it. Distinguish artifact readiness, verified behavior, and external-action authority. Prepare authorized work before required approval. If blocked by an instruction, cite its exact source and unresolved boundary; do not invent approval gates from caution.

Tool Routing

Keep the evaluation read-only. Do not create project files, roadmaps, Epics, Stories, implementation plans, campaigns, listings, advertisements, or customer outreach.

Evidence Classes

Do not turn REPORTED, ESTIMATED, or INFERRED evidence into a measured market size, search volume, conversion rate, revenue, or willingness-to-pay claim. Date every external source and distinguish the event date from the publication date when they differ. Treat the creator thesis, intended experience, taste, and conviction as owner preferences and strategic-fit inputs, never as demand, acquisition, or willingness-to-pay evidence.

Checklist

1. Frame the Decision

• Resolve the existing product or capability, target users, creator thesis, intended experience, decision horizon, available assets, geographic or regulatory scope, constraints, and explicit non-goals.
• Accept user-supplied candidates or generate a bounded set of materially distinct opportunities from product context and current signals; do not create cosmetic variants of one idea.
• Define what would justify deeper validation: identifiable user and problem, observable demand, reachable channel, credible value exchange, differentiating wedge, and affordable experiment.
• Separate discovery of a new direction from prioritization of already committed work or implementation planning.
• Record assumptions that can reverse the recommendation, separate researchable facts from owner preference, and ask one concise question only when different interpretations materially change the candidates or experiment.

2. Collect One Evidence Bundle per Candidate

• Identify who experiences the problem, how they solve it today, what triggers active search or purchase, and what evidence shows the pain is recurring or costly.
• Find a reachable acquisition channel and its mechanism: query, marketplace category, integration ecosystem, community, partner, outbound audience, or another observable path.
• Inspect direct competitors, substitutes, do-nothing behavior, pricing, positioning, distribution, review complaints, and evidence of continued investment or abandonment.
• Examine economic signals without inventing unit economics: price anchors, budget owner, purchase frequency, switching cost, delivery cost, platform fees, and support burden.
• Identify implementation, data, dependency, regulation, trust, distribution, and operational blockers that affect the cost of a validation experiment.
• Capture source/date, evidence class, scope, confidence, contradictions, and decision impact. Trace reused statistics and syndicated reports to their origin; correlated copies are one signal, not independent corroboration.
• Stop researching a candidate once the evidence is sufficient to eliminate it or additional sources cannot change its status.

3. Apply Evidence-First Elimination

• Eliminate a candidate when evidence contradicts a necessary viability condition or shows no feasible validation path within the stated constraints. Missing public data alone defers the candidate to UNKNOWN under the rule below.
• Treat competitor presence as a lead on demand and constraints; verify usage or purchase signals rather than assuming a listing proves demand. Require a concrete wedge against substitutes and doing nothing.
• Do not use universal thresholds for search volume, competitor count, ARPU, market size, or MVP duration.
• Preserve candidates with weak public data as UNKNOWN rather than labeling them invalid when a cheap primary experiment can resolve the uncertainty.
• Record the decisive evidence and falsification condition for every eliminated candidate so rejection is reproducible.
• Only after external viability, ask whether the owner is willing and able to pursue the audience, channel, operating model, and validation effort; do not infer personal interest.