| name | orec - Recommendation Generation |
| description | Generates actionable recommendations derived from findings. Takes a situation, analyzes it, and produces prioritized recommendations with implementation details and success metrics. |
| output | {"format":"prose"} |
Recommendation Generation
Input: $ARGUMENTS
Step 1: State the Situation
Establish the context that the recommendations will address.
SITUATION: [what is happening / what prompted this]
STAKEHOLDERS: [who is affected / who will act on these recommendations]
CONSTRAINTS: [budget, time, authority, technical limits]
GOAL: [what success looks like if recommendations are followed]
Step 2: Present Findings
Summarize the evidence base that recommendations will be derived from. Recommendations without findings are opinions.
FINDINGS:
1. [finding 1] — [source or evidence]
2. [finding 2] — [source or evidence]
3. [finding 3] — [source or evidence]
...
Rules:
- Each finding should be a factual statement, not an interpretation
- Cite the basis: data, observation, analysis, expert input, or user research
- Separate what is known from what is inferred
- Flag any findings with weak evidence
EVIDENCE QUALITY:
- STRONG: [findings with solid evidence]
- MODERATE: [findings with partial evidence]
- WEAK: [findings based on inference or limited data]
Step 3: Derive Recommendations
Generate recommendations directly from the findings. Each recommendation should trace back to one or more findings.
RECOMMENDATIONS:
1. [recommendation 1]
BASED ON: Finding [N], Finding [M]
TYPE: [quick win / strategic / foundational / experimental]
2. [recommendation 2]
BASED ON: Finding [N]
TYPE: [quick win / strategic / foundational / experimental]
...
Rules:
- Every recommendation must link to at least one finding
- If a recommendation has no supporting finding, it is an opinion — flag it or remove it
- Recommendations should be specific enough to act on
- Use action verbs: "Implement X", "Reduce Y", "Migrate from A to B"
Step 4: Prioritize
Rank recommendations by impact and feasibility.
| Recommendation | Impact | Effort | Priority |
|---|
| [rec 1] | [H/M/L] | [H/M/L] | [rank] |
| [rec 2] | [H/M/L] | [H/M/L] | [rank] |
DO FIRST: [high impact, low effort — quick wins]
DO NEXT: [high impact, high effort — strategic investments]
DO LATER: [low impact, low effort — nice to have]
RECONSIDER: [low impact, high effort — may not be worth it]
Step 5: Specify Implementation
For each top-priority recommendation, provide enough detail to act.
RECOMMENDATION [N]: [name]
OWNER: [who is responsible]
TIMELINE: [when to start, when to finish]
DEPENDENCIES: [what must happen first]
RESOURCES: [what is needed — people, budget, tools]
FIRST STEP: [the concrete next action to begin]
Step 6: State Expected Outcomes
Describe what changes if the recommendations are followed.
EXPECTED OUTCOMES:
- If Rec 1 is implemented: [expected result and timeframe]
- If Rec 2 is implemented: [expected result and timeframe]
- Combined effect: [what the full set of recommendations achieves together]
Step 7: Define Success Metrics
Make it possible to measure whether the recommendations worked.
SUCCESS METRICS:
1. [metric 1] — current: [baseline], target: [goal], measured by: [how]
2. [metric 2] — current: [baseline], target: [goal], measured by: [how]
...
REVIEW CADENCE: [when to check progress — weekly, monthly, quarterly]
Integration
Use with:
/rca -> Perform root cause analysis before generating recommendations/olst -> Generate a comprehensive list of possible recommendations/omtx -> Compare recommendations in a matrix/oprc -> Turn a recommendation into a detailed procedure/odec -> Frame a recommendation as a formal decision
