Sales Forecasting ModelCAUTION
1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in Anthropic's plugin directory. Plus a typed decision layer: which skill, is it safe, ship or slip. Free in-browser or npx pm-
Overview
1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in Anthropic's plugin directory. Plus a typed decision layer: which skill, is it safe, ship or slip. Free in-browser or npx pm-
8d32d25aa3f5OBSERVED · 2026-10-12What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: sales-forecasting-model description: "Build a structured sales forecast framework for any business or team. Use when asked to build a sales forecast, create a revenue model, project pipeline, or build a bottom-up forecast. Produces a forecast methodology, pipeline model, scenario analysis, and assumption log." --- # Sales Forecasting Model Skill Produces a structured sales forecast framework — from pipeline conversion modelling to scenario analysis. Built for revenue and sales leaders who need a defensible forecast, not a spreadsheet guess. ## Required Inputs Work from what is given. If any of these is missing, still produce the complete output: fill each gap with a reasonable assumption marked *(assumed, confirm)* and list those assumptions at the end. Ask a question first only when the core subject itself is missing (there is nothing to write about). - **Business type** (SaaS / Transactional / Services / Marketplace) - **Forecast period** (monthly / quarterly / annual) - **Sales motion** (inbound / outbound / channel / PLG / mixed) - **Current pipeline data** (number of deals, stages, values — rough is fine) - **Historical conversion rates** (if available — otherwise model will flag as assumption) - **Average deal size and sales cycle length** ## Output Structure --- # Sales Forecast: [Team / Business] — [Period] **Forecast type:** [Bottom-up pipeline / Top-down quota / Capacity-based / Hybrid] **Period:** [Month / Quarter / Year] **Created:** [Date] **Forecast owner:** [Name] --- ## 1. Forecast Methodology **Chosen approach:** [Bottom-up / Top-down / Hybrid] — and why for this context. Bottom-up (recommended when pipeline data exists): > Start from real deals in the pipeline. Apply stage-by-stage conversion rates. Sum to a revenue number. Top-down (useful for planning, not for calling a number): > Start from market or quota. Work backwards to activity targets. --- ## 2. Pipeline Stage Model Define the sales stages and the expected conversion rate between each: | Stage | Description | % of deals that advance | Avg time in stage | |---|---|---|---| | Prospect | Identified, not contacted | — | — | | Qualified | Discovery done, confirmed fit | [X%] | [N days] | | Proposal | Proposal sent | [X%] | [N days] | | Negotiation | Commercial terms being agreed | [X%] | [N days] | | Closed Won | Contract signed | [X%] | — | **Overall pipeline conversion rate:** [X%] (Qualified → Closed Won) **Average sales cycle:** [N days from Qualified to Close] --- ## 3. Current Pipeline Snapshot | Stage | Number of deals | Total value | Expected close (weighted) | |---|---|---|---| | Qualified | [N] | £[X] | £[X × conversion %] | | Proposal | [N] | £[X] | £[X × conversion %] | | Negotiation | [N] | £[X] | £[X × conversion %] | | **Total** | | **£[X]** | **£[weighted total]** | **Coverage ratio:** [Weighted pipeline ÷ target = X×] *Rule of thumb: 3× pipeline coverage is needed for confident forecast; 2× is tight; below 1.5× is at risk.* --- ## 4. Scenario Analysis | Scenario | Assumption | Revenue | Probability | |---|---|---|---| | Upside | All Negotiation + top 50% of Proposal close | £[X] | [%] | | Base | Weighted pipeline conversion at historical rates | £[X] | [%] | | Downside | Conversion rates drop 20% from historical | £[X] | [%] | **Committed forecast:** £[X] — [The number the forecast owner is willing to call. Between base and downside.] --- ## 5. Key Assumptions Log Every forecast is a set of assumptions. Name them explicitly so they can be updated: | Assumption | Value | Confidence | Source | Last updated | |---|---|---|---|---| | Avg deal size | £[X] | High/Med/Low | [Last N deals] | [Date] | | Sales cycle | [N days] | | | | | Close rate from Proposal | [X%] | | | | | Seasonal factor | [e.g. Q4 +20%] | | | | | Churn/contraction | [X% of ARR at risk] | | | | --- ## 6. Activity-Based Sanity Check Work backwards from the forecast to check if the required activity is achievable: To hit £[target]: - Deals needed to close: [N] (target ÷ avg deal size) - Qualified pipeline needed (at current conversion): [N deals or £value] - Discovery calls needed per week to build that pipeline: [N] - Outreach needed per week (at [X%] meeting rate): [N] **Does the team have capacity to generate this?** [Yes / No — flag if not] --- ## Quality Checks - [ ] Forecast methodology is stated (not just a number) - [ ] Stage conversion rates are based on historical data or flagged as assumptions - [ ] Coverage ratio is calculated - [ ] Three scenarios are modelled (not just one number) - [ ] Assumption log is explicit and dated - [ ] Activity sanity check confirms the forecast is achievable with current capacity ## Example Trigger Phrases - "Build a sales forecast for [period]" - "Create a pipeline model for [team/business]" - "Help me build a bottom-up revenue forecast" - "What is our forecast for Q[N] based on current pipeline?" ## Anti-Patterns - [ ] Do not present a single forecast number without scenario analysis — a forecast without upside and downside cases hides risk - [ ] Do not use 100% confidence on conversion rates that are not backed by historical data — flag them as assumptions - [ ] Do not skip the activity sanity check — a forecast number that requires unreachable activity levels is not credible - [ ] Do not use top-down quota as the only forecast method when pipeline data exists — bottom-up is more accurate and defensible - [ ] Do not omit the coverage ratio — without it, stakeholders cannot assess whether the pipeline is sufficient to hit target
Trust audit
CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | WARN |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (5)
templates/pm-discovery-agent/skills/assumption-mapper/SKILL.md
templates/pm-discovery-agent/skills/discovery-interview-guide/SKILL.md
templates/pm-discovery-agent/skills/job-story-mapper/SKILL.md
templates/pm-discovery-agent/skills/user-interview-synthesis/SKILL.md
templates/pm-launch-agent/skills/content-calendar/SKILL.md
Gates applied: no_behavioural_pass.
8d32d25aa3f5full audit observations/trust-audit/skill/mohitagw15856__sales-forecasting-model.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-12 | 8d32d25aa3f5 | CAUTION | B | 89 | first audit |
Questions
What does the Sales Forecasting Model skill do?
1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in Anthropic's plugin directory. Plus a typed decision layer: which skill, is it safe, ship or slip. Free in-browser or npx pm-
Is Sales Forecasting Model safe to install?
With care. The audit graded it B (89/100) and found 5 things worth knowing before you trust this skill, listed below with the exact line each was found on.
What can Sales Forecasting Model access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (8d32d25aa3f5), read on 2026-10-12. The repository is watched, and a new audit runs when it changes — this is the first audit.