pipeline-forecasting

pipeline-forecasting is a skill for Claude Code, Codex from guia-matthieu/clawfu-skills. It costs 18 tokens per session (1,998 once invoked), scanned A, original, MIT.

A pipeline forecast estimates future sales revenue from current opportunities, historical conversion rates, deal speed, and confidence levels.

In plain words
What is it for?
Use it for leadership reviews, board projections, quota planning, gap analysis, and best-case, worst-case, and likely-case planning.
Why use it?
It helps teams see whether the sales pipeline is likely to meet its target and where the forecast is at risk.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it for leadership reviews, board projections, quota planning, gap analysis, and best-case, worst-case, and likely-case planning.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/guia-matthieu/clawfu-skills/pipeline-forecasting
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add guia-matthieu/clawfu-skills --skill pipeline-forecasting
Clone the repo
git clone --depth 1 https://github.com/guia-matthieu/clawfu-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for pipeline-forecasting

README.md
[![agentmods](https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/pipeline-forecasting/github.svg)](https://agentmods.dev/skills/guia-matthieu/clawfu-skills/pipeline-forecasting)
Your own site
<a href="https://agentmods.dev/skills/guia-matthieu/clawfu-skills/pipeline-forecasting"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/pipeline-forecasting/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for pipeline-forecasting

Your own site · 80×15
<a href="https://agentmods.dev/skills/guia-matthieu/clawfu-skills/pipeline-forecasting"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/pipeline-forecasting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,998 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.01998
Opus 5 $0.00009 $0.00999
Sonnet 5 $0.00004 $0.00400
Haiku 4.5 $0.00002 $0.00200

Measured 9d ago against content hash eb96e897807e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

pipeline-forecasting scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/revops/pipeline-forecasting/SKILL.md · 273 lines

How it starts

The opening of the file, as written. The whole thing — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pipeline Forecasting

Build accurate, data-driven revenue forecasts using historical conversion rates, deal velocity, and confidence-weighted projections.

When to Use This Skill

  • Weekly/monthly pipeline reviews with leadership
  • Board meeting revenue projections
  • Quota setting and territory planning
  • Identifying gaps between forecast and target
  • Scenario planning for best/worst/likely outcomes

Methodology Foundation

Based on Clari's Revenue Operations methodology and Forrester's B2B Revenue Waterfall, combining:

  • Weighted pipeline (probability × value)
  • Historical stage conversion rates
  • Deal velocity analysis
  • Commit vs. upside categorization

What Claude Does vs What You Decide

Claude Does You Decide
Calculates weighted pipeline by stage Which deals to include/exclude
Applies historical conversion rates Override factors for specific deals
Generates confidence intervals Final commit number to leadership
Identifies forecast risks Actions to close gaps
Models best/worst/likely scenarios Which scenario to plan against

What This Skill Does

  1. Ingests pipeline data - Current opportunities with stage, value, close date
  2. Applies conversion math - Historical win rates by stage, segment, rep
  3. Calculates weighted forecast - Probability-adjusted revenue projection
  4. Generates scenarios - Best case, commit, worst case with confidence bands
  5. Identifies risks - Deals pushing, pipeline gaps, coverage ratios

How to Use

I need a pipeline forecast for Q1. Here's our current pipeline:

[Paste pipeline data: Deal name, Stage, Value, Close Date, Rep]

Historical context:
- Average win rate: 25%
- Stage 3→Close rate: 45%
- Stage 4→Close rate: 70%
- Average sales cycle: 45 days

Target: $2.5M for Q1

Instructions

Step 1: Pipeline Categorization

Segment deals into:

  • Commit - High confidence (Stage 4+, verbal commit)
  • Best Case - Medium confidence (Stage 3, engaged)
  • Upside - Low confidence (Stage 1-2, early)

Read the full file on GitHub · 273 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 273 lines · 18 tokens per session scan A eb96e897807e

Subscribe to this mod's changes

pipeline-forecasting is a skill published in the GitHub repository guia-matthieu/clawfu-skills (149 stars, last pushed 5mo ago), licensed MIT. It adds 18 tokens to every session and 1,998 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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