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Grok Bot+18 agentsRecommendation Builder Pro
Turn evidence and trade-offs into prioritized recommendations, practical actions, owners, and measures.
$9.99
Recommendation Builder Pro
Example session with this skill installed
A small support team received 900 tickets last month. 62% were password-reset questions, median first response was 19 hours, and 35% were resolved by the first reply. Leadership can either improve help-center instructions, add a password-reset flow, or schedule one extra support shift. Budget and implementation capacity are limited but not quantified. Compare options, identify data gaps, and recommend a low-risk next step with measures; do not assume cost or causation.
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- Compiled the recommendation builder pro
Support Response Improvement Recommendation
Decision
Choose a short, measured help-center improvement pilot first, while collecting the data needed to compare a self-service flow and staffing change. This is a provisional recommendation because budget, implementation effort, ticket timing, and user outcomes are not quantified.
Evidence and gaps
- 900 tickets were received last month.
- Password-reset questions represented 62% (558 tickets if the percentage is exact).
- Median first response was 19 hours.
- 35% were resolved by the first reply.
- Unknown: first-response and resolution rates by ticket type, repeat contacts, article usage, implementation effort, peak-hour demand, and user success. These figures do not establish why response time is high.
| Option | Potential value | Key uncertainty | Reversible first step |
|---|---|---|---|
| Improve help-center instructions | May help users find current reset steps. | Whether content is discoverable and solves the issue. | Review search terms and test revised instructions with a small user group. |
| Add reset flow | Could reduce manual work if technically feasible. | Engineering cost, security requirements, and adoption. | Request a scoped feasibility and security review before committing. |
| Add support shift | Could cover peak demand if tickets cluster in specific hours. | Staffing cost, schedule, and demand distribution. | Analyze hourly arrivals and response times before scheduling. |
Pilot and measures
Update one approved instruction page and measure page visits, successful self-reported resets, related ticket volume, repeat contacts, and time to resolution for four weeks. Compare with a similar prior period and note releases, seasonality, and incident spikes. Do not infer causation from one before-and-after comparison.
Decision trigger
If users cannot complete the reset or security needs are unclear, pause the content change and ask the product/security owner to evaluate a flow. If after-hours ticket concentration is high, model staffing against actual arrivals and costs. The budget owner approves any spend.
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About this skill
Recommendation Builder Pro
Turn analysis, constraints, and decision criteria into clear, prioritized recommendations people can implement. Make the evidence trail, assumptions, trade-offs, and unresolved questions explicit.
Deliverables
- Decision question and criteria
- Options comparison with evidence and confidence
- Recommended action and rationale
- Implementation steps, owners, and dependencies
- Risks, measures, and review trigger
Workflow
- Clarify who decides, what outcome matters, and by when.
- Separate verified facts, assumptions, and unknowns.
- Compare feasible options against agreed criteria and constraints.
- Recommend an option with a clear rationale, downside, and fallback.
- Convert it into sequenced actions, owners, measures, and a reassessment date.
Guardrails
Do not claim certainty beyond the evidence or hide material trade-offs. Flag regulated, legal, financial, or safety-sensitive choices for qualified review. The decision owner approves the recommendation.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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