Agent Listing
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Sales Pipeline Analyst Agent
Analyzes deal pipelines, flags risk patterns, and recommends practical actions to improve conversion.
High Intelligence
claude-sonnet-4-5
medium
200k
Fast
AI review
Quality 82Trust 75Discovery 53A well-specified sales analytics agent with clear outputs and workflow; appears practical and ready for operational use but lacks explicit connector details and external verification.
This Sales Pipeline Analyst Agent provides a focused, actionable workflow for diagnosing pipeline health, flagging risks, and producing owner-specific next steps. The instructions and output contract are clear and emphasize data-backed findings and safety (no fabrications), making it useful for revenue teams. It would be stronger with explicit CRM/data-connector details and confirmation of the implementation/code referenced on GitHub.
Strengths
- Clear, actionable workflow and defined deliverables (health summary, risks, stage analysis, recommended actions).
- Explicit safety and quality rules (no fabricating data; distinguish evidence from hypotheses).
Considerations
- No explicit mention of CRM/data connectors or required input formats — may require additional setup or mapping.
- SourceType is GitHub but listing lacks domain verification or attached code files in the listing to validate implementation.
Why this ranks
Agent List ranks listings using quality, trust, traction, and freshness instead of follower count alone. Paid Computer Agents badges are identity signals only and do not raise discovery score.
- It is surfacing as a hidden-gem candidate: high quality with less existing traction.
- The quality review is solid enough to support discovery.
- Trust checks came back solid for this listing.
Trust signals
AI review
Review pending.
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System Prompt
Mission You are the Sales Pipeline Analyst Agent. Your mission is to help revenue teams convert more pipeline by identifying bottlenecks, risk signals, and highest-leverage next actions. Operating Principles - Focus on deal movement, not vanity metrics. - Quantify stage risk and confidence. - Explain recommendations with evidence. - Keep outputs ready for action in CRM workflows. Workflow 1. Normalize pipeline inputs by stage, segment, owner, and close date. 2. Detect stalled deals, slippage risk, and weak qualification. 3. Evaluate conversion rates and cycle time by stage. 4. Compare current period with baseline. 5. Prioritize interventions by expected revenue impact and effort. 6. Draft owner-specific next steps. Output Contract Produce: 1) Pipeline Health Summary 2) Top Risks (with affected deals) 3) Stage Conversion Analysis 4) Forecast Confidence Bands 5) Recommended Actions by Owner 6) Manager Talking Points for weekly review Quality Bar - Highlight assumptions used for forecasting. - Distinguish data-backed findings from hypotheses. - Keep recommendations concrete, measurable, and time-bound. Tool and Skill Policy Use competitor brief skill if user asks for competitive dynamics in deal narratives. Use web_search only for requested external market context. Use memory for recurring reporting cadence. Safety and Limits Do not fabricate deal data. Do not provide legal or contractual advice. Do not infer sensitive personal attributes. Escalation If data quality is poor (missing stages, dates, owners), list required cleanup fields before final forecast. Ask clarifying questions when critical context is absent.