Installation
npx skills add sales-skills/sales --skill sales-forecast 29
Installs
Build a Revenue Forecast
Help the user build and validate a revenue forecast — from category modeling through pipeline coverage analysis, deal-level inspection, and gap planning.
Step 1 — Gather context
Ask the user:
Scope:
- A) Individual rep forecast
- B) Team / pod forecast
- C) Regional forecast
- D) Company-wide forecast
Time period:
- Current quarter
- Next quarter
- Half / full year
- Custom period
What numbers do you have? (provide what you know)
- Quota / target
- Closed-won so far this period
- Commit (deals you're confident will close)
- Best case (deals that could close with things going right)
- Total open pipeline
- Average sales cycle length
- Historical win rate
What's your primary concern?
- A) We're behind quota and need a gap plan
- B) I need to validate my commit number
- C) I need to present a forecast to leadership
- D) Pipeline coverage feels thin
- E) Too many deals are slipping from commit to best case
- F) Other — describe it
If the user's request already provides most of this context, skip directly to the relevant step. Lead with your best-effort answer using reasonable assumptions (stated explicitly), then ask only the most critical 1-2 clarifying questions at the end — don't gate your response behind gathering complete context.
Step 2 — Forecast model
Build a forecast model table:
| Category | # Deals | Total Value | Win Probability | Weighted Value |
|---|---|---|---|---|
| Closed Won | 100% | |||
| Commit | 85-95% | |||
| Best Case | 40-60% | |||
| Pipeline (Stage 3+) | 15-30% | |||
| Early Pipeline (Stage 1-2) | 5-10% | |||
| Upside (not in pipeline yet) | 2-5% |
These are typical probability ranges — adjust based on the team's historical conversion data if available. Teams with strong qualification tend toward the higher end; teams early in building pipeline discipline should use the lower end.
Forecast summary
| Metric | Value |
|---|---|
| Quota | |
| Closed Won | |
| Weighted forecast (sum of weighted values) | |
| Expected outcome (most likely landing zone) | |
| Gap to quota | |
| Coverage ratio (total pipeline / remaining quota) | |
| Commit coverage (commit / remaining quota) |
Forecast scenarios
- Worst case: Closed Won + (Commit × 80%) — assumes some commit deals slip
- Most likely: Closed Won + (Commit × 90%) + (Best Case × 40%)
- Best case: Closed Won + (Commit × 95%) + (Best Case × 60%) + (Pipeline × 15%)
Present as a range: "Based on current pipeline, expect to land between $X (worst) and $Y (best), most likely around $Z."
Step 3 — Pipeline coverage analysis
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Coverage ratio (pipeline / quota) | 3-4x for new business, 2-3x for expansion | Green/Yellow/Red | |
| Commit coverage (commit / remaining gap) | 1.0x+ means commit covers the gap | ||
| Average deal size | Compare to quota-required deal size | ||
| Average cycle length | Deals must have enough runway to close in period | ||
| Win rate | Historical vs. current period | ||
| Pipeline creation rate | $ created per week/month — is it accelerating or slowing? | ||
| Stage conversion rates | Stage 1→2, 2→3, 3→4, etc. — where are deals stalling? |
Coverage analysis rules
- Coverage < 2x: Critical — not enough pipeline to hit quota even optimistically. Immediate pipeline generation needed.
- Coverage 2-3x: Thin — likely to miss unless win rates are above average. Focus on deal acceleration and pipeline gen.
- Coverage 3-4x: Healthy for new business — focus on execution and deal quality.
- Coverage 4x+: Strong coverage — focus on deal progression and closing, not more pipeline.
- Commit > remaining gap: You have enough in commit to cover the gap. Focus shifts to deal execution and preventing slippage.
- Deals closing after period end: Flag any "commit" deals with close dates after the period ends — these aren't real commit.
Step 4 — Deal-level inspection
For each deal in Commit and Best Case, create an inspection table:
| Deal | Value | Stage | Days in stage | Close date | Risk flags | Confidence |
|---|---|---|---|---|---|---|
| High/Med/Low |
Risk flags to check
- Close date pushed more than once
- No activity in 14+ days
- Single-threaded (one contact)
- No compelling event
- In stage longer than 2x average
- Economic buyer not engaged
- Competitor mentioned but not addressed
- Budget not confirmed
Recommendations per deal
For each deal, recommend one of:
- Keep in Commit: Strong deal, high confidence, clear path to close
- Move to Best Case: Has potential but too many open risks for commit
- Move to Pipeline: Significant unknowns — not ready for commit or best case
- Pull in: Deal could close faster than planned — what would accelerate it?
- Push to next period: Won't close this period — move out and plan accordingly
- Qualify out: Deal isn't real — remove from pipeline
Step 5 — Gap plan
If there's a gap between the forecast and quota, build a plan to close it:
| Lever | Description | Potential value | Actions | Timeline |
|---|---|---|---|---|
| Pull-in | Accelerate deals currently slated for next period | Identify 2-3 deals that could close sooner with the right push (executive meeting, POC, special terms) | This week | |
| Accelerate stalls | Reactivate stalled pipeline deals | Re-engage with new value prop, bring in executive sponsor, offer assessment/workshop | 2 weeks | |
| Expansion | Upsell/cross-sell existing customers | Identify customers with low product adoption, recent growth, or upcoming renewal | 2-4 weeks | |
| New outbound | Create new pipeline via outbound | Blitz campaign to high-intent accounts, leverage trigger events (funding, hiring, tech changes) | 4-8 weeks | |
| Partner/referral | Source deals through partners or referrals | Activate partner relationships, request customer referrals, co-sell with tech partners | 2-6 weeks |
For each lever, answer:
- How much can it realistically contribute? (be conservative — gap plans are usually optimistic)
- What specific actions will you take this week? (not "do more outbound" — specific companies, people, messages)
- Who owns it? (rep, manager, SE, executive)
- When will you know if it's working? (set a checkpoint date)
Gap plan math
- Gap: Quota − (Closed Won + Weighted Commit + Weighted Best Case)
- Gap plan target: Gap × 1.5 (plan for more than you need, since not all levers will work)
- Minimum viable gap close: At least 50% of gap plan should come from Pull-in and Accelerate (fastest to materialize)
Related skills
/sales-salesloft— Salesloft Forecast module for submission workflows and AI-assisted predictions/sales-deal-inspect— Deep-dive on individual deals in your forecast/sales-pipeline— Portfolio-level pipeline management and deal prioritization/sales-cadence— Build outbound cadences for gap-plan pipeline generation/sales-close— Closing strategies for commit deals/sales-do— Not sure which skill to use? The router matches any sales objective to the right skill. Install:npx skills add sales-skills/sales --skills sales-do
Gotchas
- Don't use pipeline total without weighting by stage. Claude will sometimes say "you have $2M in pipeline against a $1M quota, so you're covered." Raw pipeline total is meaningless — only weighted pipeline matters. Always apply stage-based win probabilities.
- Don't assume historical win rates apply to the current quarter. Win rates shift based on deal mix, market conditions, new competitors, and team changes. If the user provides historical rates, use them as a starting point but flag that current-quarter dynamics may differ.
- Don't forget to account for slipped deals from last quarter. Deals that pushed from last quarter inflate current-quarter pipeline but often have lower close probability (they already missed one deadline). Flag these and weight them more conservatively.
- Don't ignore seasonality. Q4 and fiscal year-end typically see higher close rates due to budget pressure. Q1 often sees longer cycles as budgets reset. Ask about the company's fiscal year when it matters.
- Don't present a single forecast number without a range. Always give worst/most likely/best case scenarios. A single number creates false precision and sets the user up for a bad forecast call.
Examples
Example 1: Quarterly forecast build
User says: "Build my team's Q2 forecast. Quota is $2M, we've closed $800k, commit is $600k across 4 deals, best case is $400k, total pipeline is $1.8M, 6 weeks left."
Skill does:
- Builds a forecast model with weighted values across all categories
- Calculates coverage ratio (1.5x — flags as thin)
- Presents worst/most likely/best case scenarios
- Creates a gap plan with specific levers to close the gap
Result: Complete forecast ready for the leadership call, with a gap plan if needed
Example 2: Commit validation
User says: "Validate my $500k commit — Deal A ($200k, negotiation, strong champion), Deal B ($150k, proposal, no EB meeting), Deal C ($150k, demo stage, verbal interest only)."
Skill does:
- Inspects each deal against risk criteria
- Recommends keeping Deal A in commit, moving Deal B to best case, moving Deal C to pipeline
- Adjusts commit to $200-350k with reasoning
Result: Defensible commit number the rep can present to their manager
Troubleshooting
Don't have all the numbers
Solution: Start with what you know. The skill can build a useful forecast from just quota + closed-won + pipeline total. It will flag what's missing and estimate where possible. Even a rough forecast with assumptions stated is better than no forecast.
Forecast keeps missing — always too optimistic
Solution: Apply stricter win probability weights. Most teams over-weight commit (use 85% not 95%) and best case (use 40% not 60%). Check for "commit creep" — deals that sit in commit for multiple forecast periods without closing. The deal-level inspection step catches these patterns.
Gap plan feels unrealistic
Solution: Apply the 50% rule — at least half of gap plan value should come from pull-in and accelerate levers (fastest to materialize). New outbound takes 4-8 weeks to generate pipeline, so it won't help this quarter. Be conservative on each lever and plan for 1.5x the gap.
Installs
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View Source
sales-skills/sales
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How to use this skill
Install sales-forecast by running npx skills add sales-skills/sales --skill sales-forecast in your project directory. Run the install command above in your project directory. The skill file will be downloaded from GitHub and placed in your project.
No configuration needed. Your AI agent (Claude Code, Cursor, Windsurf, etc.) automatically detects installed skills and uses them as context when generating code.
The skill enhances your agent's understanding of sales-forecast, helping it follow established patterns, avoid common mistakes, and produce production-ready output.
What you get
Skills are plain-text instruction files — not executable code. They encode expert knowledge about frameworks, languages, or tools that your AI agent reads to improve its output. This means zero runtime overhead, no dependency conflicts, and full transparency: you can read and review every instruction before installing.
Compatibility
This skill works with any AI coding agent that supports the skills.sh format, including Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider, and other tools that read project-level context files. Skills are framework-agnostic at the transport level — the content inside determines which language or framework it applies to.
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