daddia Set Targets
When to use
Attach baseline, target, commit/aspirational label, and scoring formula — same number means opposite things without commitment level.
What this skill does not do
- Does not instrument metrics — route unknown baselines to
/okr:instrument-metricsfirst. - Does not write KRs — route to
/okr:write-key-results. - Does not score the cycle — route to
/okr:score-and-retro.
Preconditions
| Input | If missing |
|---|---|
| KRs with known baselines | Halt — route to instrument-metrics |
| Practice profile (philosophy, formula) | Default linear interpolation; tag [PROVISIONAL] |
| Explicit commit/aspirational label per KR | Ask — do not infer from number |
Provisional mode
Without seed history: set-level sandbagging check limited to trivial-target flags on current set.
Trust spine
- Confidence bands (
governance-tracking):- High: Every KR has type, baseline, target, formula, calibration flag.
- Medium: Some calibration flags on commit/aspirational mismatch.
- Low: Baselines unknown — halt, route to instrument-metrics.
- Failure modes:
- Strategic advice vs. support: Targets are draft for calibration approval.
- Client confidentiality: Targets may be pre-approval — CONFIDENTIAL header.
- Accountability gap: Sandbagging patterns named, not praised.
- Analytical Rigor: N/A — governance shape.
- Incentive Gaming: Guards sandbagging — trivial aspirational targets and commit labels on stretch goals flagged.
- Escalation triggers: Consistent ~1.0 history in seed data — name sandbagging pattern for calibration.
Workflow
- Read practice profile for philosophy and scoring formula.
- Get explicit commit/aspirational label per KR — don't infer.
- Set baseline and target — halt if baseline unknown.
- State scoring formula alongside each KR.
- Calibration check: commits realistic? aspirational genuinely stretch? history of ~1.0?
- Gaming-pattern check before output.
Output format
CONFIDENCE: [defensible recommendation | structured first pass]
LOAD-BEARING ASSUMPTIONS: [if any]
KR: [text]
Type: [commit | aspirational]
Baseline: [value] → Target: [value]
Scoring formula: [from profile]
Calibration flag: [none | trivial aspirational | unrealistic commit | baseline unknown]
[repeat per KR]
SET-LEVEL PATTERN CHECK: [sandbagging or overreach history if seed data exists]
Worked example
Input: Aspirational KR "NPS 50." Baseline 38. Target 40 (2pt lift).
Expected output (excerpt):
KR: NPS 50
Type: aspirational
Baseline: 38 → Target: 40
Scoring formula: linear interpolation
Calibration flag: target looks trivial for an aspirational KR [review]
Quality checks before delivering
- Commit/aspirational explicit per KR
- Baselines known or routed to instrument-metrics
- Formula stated per KR
- Calibration flags applied
- Sandbagging pattern named if history supports it
- Gaming-pattern check run
Propose profile update
When a stable convention surfaces during this run (thresholds, naming, tone, output format, or recurring corrections), propose a profile update: show the exact diff against ~/.claude/plugins/config/claude-for-strategy/okr/CLAUDE.md (org-wide facts go to org-profile.md), ask for confirmation, and write only on yes. Only /okr:practice-setup auto-applies a full profile write.
Outputs
Follows plugin CLAUDE.md § Outputs. Next: calibration approval, check-in cadence, or revise targets.