Fetches forecast from anthropics/knowledge-work-plugins and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/forecast
Restart Cursor to activate forecast. Access via /forecast in your agent's command palette.
⚠
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Generate a weighted sales forecast with risk analysis and commit recommendations.
Usage
/forecast [period]
Generate a forecast for: $ARGUMENTS
If a file is referenced: @$1
How It Works
┌─────────────────────────────────────────────────────────────────┐
│ FORECAST │
├─────────────────────────────────────────────────────────────────┤
│ STANDALONE (always works) │
│ ✓ Upload CSV export from your CRM │
│ ✓ Or paste/describe your pipeline deals │
│ ✓ Set your quota and timeline │
│ ✓ Get weighted forecast with stage probabilities │
│ ✓ Risk-adjusted projections (best/likely/worst case) │
│ ✓ Commit vs. upside breakdown │
│ ✓ Gap analysis and recommendations │
├─────────────────────────────────────────────────────────────────┤
│ SUPERCHARGED (when you connect your tools) │
│ + CRM: Pull pipeline automatically, real-time data │
│ + Historical win rates by stage, segment, deal size │
│ + Activity signals for risk scoring │
│ + Automatic refresh and tracking over time │
└─────────────────────────────────────────────────────────────────┘
What I Need From You
Step 1: Your Pipeline Data
Option A: Upload a CSV
Export your pipeline from your CRM (e.g. Salesforce, HubSpot). I need at minimum:
Deal/Opportunity name
Amount
Stage
Close date
Helpful if you have:
Owner (if team forecast)
Last activity date
Created date
Account name
Option B: Paste your deals
Acme Corp - $50K - Negotiation - closes Jan 31
TechStart - $25K - Demo scheduled - closes Feb 15
BigCo - $100K - Discovery - closes Mar 30
Option C: Describe your territory
"I have 8 deals in pipeline totaling $400K. Two are in negotiation ($120K), three in evaluation ($180K), three in discovery ($100K)."
Step 2: Your Targets
Quota: What's your number? (e.g., "$500K this quarter")
Timeline: When does the period end? (e.g., "Q1 ends March 31")
Already closed: How much have you already booked this period?
Output
# Sales Forecast: [Period]**Generated:** [Date]
**Data Source:** [CSV upload / Manual input / CRM]
---## Summary| Metric | Value ||--------|-------||**Quota**| $[X] ||**Closed to Date**| $[X] ([X]% of quota) ||**Open Pipeline**| $[X] ||**Weighted Forecast**| $[X] ||**Gap to Quota**| $[X] ||**Coverage Ratio**| [X]x |---## Forecast Scenarios| Scenario | Amount | % of Quota | Assumptions ||----------|--------|------------|-------------||**Best Case**| $[X] | [X]% | All deals close as expected ||**Likely Case**| $[X] | [X]% | Stage-weighted probabilities ||**Worst Case**| $[X] | [X]% | Only commit deals close |---## Pipeline by Stage| Stage |# Deals | Total Value | Probability | Weighted Value ||-------|---------|-------------|-------------|----------------|| Negotiation | [X] | $[X] | 80% | $[X] || Proposal | [X] | $[X] | 60% | $[X] || Evaluation | [X] | $[X] | 40% | $[X] || Discovery | [X] | $[X] | 20% | $[X] ||**Total**| [X] | $[X] | — | $[X] |---## Commit vs. Upside### Commit (High Confidence)Deals you'd stake your forecast on:
| Deal | Amount | Stage | Close Date | Why Commit ||------|--------|-------|------------|------------|| [Deal] | $[X] | [Stage] | [Date] | [Reason] |**Total Commit:** $[X]
### Upside (Lower Confidence)Deals that could close but have risk:
| Deal | Amount | Stage | Close Date | Risk Factor ||------|--------|-------|------------|-------------|| [Deal] | $[X] | [Stage] | [Date] | [Risk] |**Total Upside:** $[X]
---## Risk Flags| Deal | Amount | Risk | Recommendation ||------|--------|------|----------------|| [Deal] | $[X] | Close date passed | Update close date or move to lost |
✓
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
›Access to product documentation and roadmap tools (Jira, Notion, etc.)
›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
1Install product management skill
2Start with user story generation for known feature
3Progress to competitive analysis: research 2-3 competitors
4Use for roadmap prioritization: apply RICE/ICE scoring
5Draft stakeholder communications and refine based on feedback
6Build template library for recurring PM tasks
7Share effective prompts with product team
Common Pitfalls
⚠Not validating competitive research—verify facts before sharing
⚠Accepting user stories without involving engineering team
⚠Over-relying on frameworks without qualitative judgment
⚠Not customizing outputs to company culture and communication style
⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
+Validate research and competitive analysis with real data
+Collaborate with engineering when generating technical requirements
+Customize frameworks and templates to your company context
+Use skill for first drafts, refine with stakeholder input
+Document successful prompt patterns for PM tasks
+Combine AI efficiency with human judgment and intuition
✗ Don't
−Don't publish competitive analysis without fact-checking
−Don't finalize user stories without engineering review
−Don't make prioritization decisions solely on AI scoring
−Don't skip customer validation of generated requirements
−Don't ignore company-specific context and culture
💡 Pro Tips
★Provide context: company goals, constraints, customer feedback
★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
1Basic: user stories, feature specs, status updates
