codexkit-sales-forecast-analyzer

codexkit-sales-forecast-analyzer is a skill for Claude Code, Codex from hoavdc/CodexKit. It costs 40 tokens per session (882 once invoked), scanned A, original, MIT.

A sales forecast analyzer turns sales pipeline and past revenue data into estimates for future revenue. It separates completed sales from open opportunities and can compare base, upside, and downside scenarios.

In plain words
What is it for?
Use it to prepare sales reviews, group opportunities by stage or owner, apply historical or pipeline-based forecasting, explain forecast movement, and create scenario ranges.
Why use it?
It makes uncertain revenue estimates easier to review by showing the assumptions, data gaps, and changes behind the forecast.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/hoavdc/codexkit/codexkit-sales-forecast-analyzer
Any agent
npx skills add hoavdc/CodexKit --skill codexkit-sales-forecast-analyzer
Clone the repo
git clone --depth 1 https://github.com/hoavdc/CodexKit

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 codexkit-sales-forecast-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/hoavdc/codexkit/codexkit-sales-forecast-analyzer.svg)](https://agentmods.dev/skills/hoavdc/codexkit/codexkit-sales-forecast-analyzer)
Your own site
<a href="https://agentmods.dev/skills/hoavdc/codexkit/codexkit-sales-forecast-analyzer"><img src="https://agentmods.dev/badge/skills/hoavdc/codexkit/codexkit-sales-forecast-analyzer.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 882 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00040 $0.00882
Opus 5 $0.00020 $0.00441
Sonnet 5 $0.00008 $0.00176
Haiku 4.5 $0.00004 $0.00088

Measured yesterday against content hash 5efcfe959cfd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codexkit-sales-forecast-analyzer 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 yesterday.

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/codexkit-sales-forecast-analyzer/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Sales Forecast Analyzer

When to Use

  • Forecasting revenue from historical sales or active pipeline.
  • Preparing weekly, monthly, or quarterly sales reviews.
  • Comparing committed, best-case, and upside scenarios.
  • Explaining forecast movement to founders, finance, RevOps, or sales leadership.

Procedure

Step 1 - Normalize Inputs

Separate actuals, pipeline, assumptions, and qualitative signals. Do not mix closed revenue with open pipeline.

Step 2 - Segment The Pipeline

Group opportunities by stage, close date, owner, segment, product, and confidence where available.

Step 3 - Apply Forecast Logic

Choose the simplest defensible method:

  • historical trend for stable recurring sales
  • stage-weighted pipeline for active opportunities
  • rep commit for manager-reviewed forecast
  • scenario range when inputs are uncertain

Step 4 - Explain Drivers

Identify the movement drivers:

  • new pipeline
  • slipped deals
  • closed-won / closed-lost
  • expansion / contraction
  • conversion rate change
  • average deal size change

Step 5 - Produce Scenarios

Provide Base, Upside, and Downside scenarios with assumptions and confidence. Flag data quality gaps.

Inputs

Input Required Format
Historical sales Recommended Period, revenue, bookings, units
Pipeline Recommended Deal, amount, stage, probability, close date
Sales cycle assumptions Optional Win rate, stage duration, seasonality
Forecast horizon Yes Month, quarter, year
Business context Optional Promotions, market changes, hiring, capacity

Output

## Sales Forecast - [Period]

### Executive Summary
[Forecast number, confidence, main movement drivers]

### Scenario Forecast
| Scenario | Forecast | Assumptions | Confidence |
|----------|----------|-------------|------------|

### Pipeline Movement
| Driver | Impact | Notes |
|--------|--------|-------|

### Risks And Watch Items
- [Risk] - [mitigation]

### Data Quality Notes
- [Missing fields, stale opportunities, probability caveats]

Read the full file on GitHub · 122 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. yesterday First seen · 122 lines · 40 tokens per session scan A 5efcfe959cfd

Subscribe to this mod's changes

codexkit-sales-forecast-analyzer is a skill published in the GitHub repository hoavdc/CodexKit (21 stars, last pushed 3mo ago), licensed MIT. It adds 40 tokens to every session and 882 once invoked, about $0.0002 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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