ln-72-product-outcome-evaluator

Installation
SKILL.md

Product Outcome Evaluator

Goal: Determine what available evidence supports about a delivered product outcome and recommend continuation, adjustment or stopping. Remain read-only: do not change instrumentation, experiments, user treatment, campaigns or product files.

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

Need Preferred capability Fallback
Original hypothesis Product intent, baseline, experiment/measurement plan and accepted targets Reconstruct from attributable sources; keep missing targets unknown
Outcome evidence Authorized analytics, experiment results, customer behavior and cost/support evidence Sanitized exports with explicit measurement limits
Analysis Reproducible queries/statistics appropriate to the study design Transparent arithmetic and qualitative inference; no fabricated causal confidence
Installs
7
GitHub Stars
569
First Seen
Sep 14, 2026
ln-72-product-outcome-evaluator — levnikolaevich/claude-code-skills