| name | measure-okr-grader |
| description | Scores completed OKR sets at cycle close with KR-level scoring per the canonical OKR type enum (committed | aspirational | learning | operational_health | compliance_or_safety), committed-vs-aspirational interpretation, evidence quality assessment, learning synthesis, and next-cycle recommendations. Refuses to retroactively change targets or shrink committed scope, average away guardrail KRs, treat 0.7 as success for committed or compliance_or_safety KRs, equate effort with impact, or use scores for individual performance. Hands off to iterate-lessons-log, iterate-retrospective, define-hypothesis, measure-dashboard-requirements, measure-instrumentation-spec, and foundation-okr-writer. |
| phase | measure |
| version | 1.0.0 |
| updated | 2026-05-01T00:00:00.000Z |
| license | Apache-2.0 |
| metadata | {"category":"reflection","frameworks":["triple-diamond","okrs","lean-startup"],"author":"product-on-purpose"} |
OKR Grader
An OKR Cycle Review is a backward-looking artifact that closes the loop on a completed OKR set. It scores each KR against its baseline and target, separates committed from aspirational interpretation, surfaces what evidence does and does not support, names what the team learned, and prepares input for next-cycle drafting. Done well, a cycle review protects the integrity of the OKR operating system by refusing to dress up missed commitments as aspirational stretch, refusing to celebrate effort over outcome, and refusing to let scoring carry weight it cannot bear.
This skill is an evidence interpreter, not an arithmetic engine. Its job is to read final KR values, compare them against the original OKR set's intent, and produce a review that names the learning honestly. It enforces the empirical scoring conventions drawn from Doerr (Measure What Matters), Wodtke (Radical Focus), Castro (committed vs aspirational interpretation), Grove (High Output Management), and the OKR community's accumulated practice on misuse failure modes. It pairs with foundation-okr-writer (which produced the OKR set being scored) and hands off the learnings produced here to the iterate skills that consume them.
When to Use
- The OKR cycle has ended (or you are scoring a partial-cycle close)
- You have final or interim KR values, baselines, and targets
- Stakeholders need a clear review with score, evidence, and learning
- The team is deciding what to continue, stop, change, or carry forward
- There is disagreement about whether a score is good or bad
- Evidence quality across KRs is uneven and needs to be made visible
When NOT to Use
- You are still drafting OKRs . use
/okr-writer
- You want a generic team retro . use
/retrospective
- You are reporting a single experiment result . use
/experiment-results
- You need a stakeholder progress update without scoring . use
/stakeholder-update
- The OKR set was never agreed on or never tracked . scoring requires an authored set; backfill via
/okr-writer first
- You want to use scores to evaluate individuals . the skill refuses this
Instructions
When asked to score completed OKRs, follow these steps:
-
Validate scoring readiness
Check inputs: original OKR set, cycle dates, final KR values (or interim values for partial-close), baselines, targets, evidence sources, and OKR types (committed | aspirational | learning | operational_health | compliance_or_safety). If a value is missing, mark it explicitly (, , ); never fabricate. Refuse to grade KRs whose original definitions are missing entirely.
