dr-forecast-variance

dr-forecast-variance is a skill for Claude Code, Codex from Datarails/dr-claude-code-plugins-re. It costs 28 tokens per session (9,731 once invoked), scanned B, original, MIT.

A comparison of actual results with planned and forecast results for a chosen year or period.

In plain words
What is it for?
Use it for financial planning, performance reviews, and examining differences between available scenarios, with optional Excel and PowerPoint outputs.
Why use it?
It shows where performance differs from expectations and helps identify changes that may need review.

Skill for Claude CodeCodex

Part of the datarails-financeos plugin — 19 skills, 4 commands shipped together

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/datarails/dr-claude-code-plugins-re/forecast-variance
Any agent
npx skills add Datarails/dr-claude-code-plugins-re --skill forecast-variance
Clone the repo
git clone --depth 1 https://github.com/Datarails/dr-claude-code-plugins-re

Made for: Claude Code, Codex.

Or install datarails-financeos, the plugin that ships this one along with the rest of its 19 skills, 4 commands.

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 dr-forecast-variance

README.md
[![agentmods](https://agentmods.dev/badge/skills/datarails/dr-claude-code-plugins-re/forecast-variance.svg)](https://agentmods.dev/skills/datarails/dr-claude-code-plugins-re/forecast-variance)
Your own site
<a href="https://agentmods.dev/skills/datarails/dr-claude-code-plugins-re/forecast-variance"><img src="https://agentmods.dev/badge/skills/datarails/dr-claude-code-plugins-re/forecast-variance.svg" alt="Measured on agentmods" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 9,731 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. 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 $0.00028 $0.09731
Opus 5 $0.00014 $0.04866
Sonnet 5 $0.00006 $0.01946
Haiku 4.5 $0.00003 $0.00973

Measured 4d ago against content hash f810db85a95a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

dr-forecast-variance scanned grade B with 1 finding 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 4d 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.

Subtle steeringmediumPrompt injection

Instructions that bias recommendations or shape behaviour without the user noticing.

> **Do NOT gate analysis on `isConnected`.** Refresh, DR-formula reads, evaluate **and drill-down** all work on an unconnected workbook. `connect_file` is required **only** for `create_dynamic_range`, and **only on COM**
skills/forecast-variance/SKILL.md · 555 lines

How it starts

The opening of the file, as written. The whole thing — 555 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Forecast Variance Analysis

Analyze variances between your actual, plan, and forecast data. Scenario names are discovered from your data, never assumed — many orgs have no Budget scenario at all (plan data often lives in a separate planning-version field), so the plan side of the comparison is resolved at runtime (Step 1b).

Essential for FP&A reviews, planning adjustments, and performance tracking.

Arguments

Argument Description Default
--year <YYYY> REQUIRED Calendar year to analyze
--scenarios <list> Comma-separated scenario names, resolved against the discovered scenario domain (Step 1b) Resolved at runtime — actual side + plan side + forecast, whichever exist
--period <YYYY-MM> Specific period to focus on All year
--output-xlsx <file> Excel output path tmp/Forecast_Variance_YYYY_TIMESTAMP.xlsx
--output-pptx <file> PowerPoint output path tmp/Forecast_Summary_YYYY_TIMESTAMP.pptx

Excel Context Mode (Claude in Excel)

When this skill is invoked from within Claude in Excel (the task pane add-in), switch to in-sheet enrichment mode instead of generating output files. This mode integrates the row-commentary approach from datarails-excel-multi-table-analysis and is the preferred mode when the user is working directly in a workbook.

How to detect the context: Excel context mode activates when the user has an open workbook and wants in-sheet enrichment — with or without an existing range. This applies in Claude for Excel (task pane), Claude Code with an open workbook, or any context where the user is working directly in a spreadsheet. Do not generate .xlsx or .pptx output files. Write all output directly into the active workbook using whichever Excel cell-write tool is available to you. Never use the Write tool to write spreadsheet content in this context. If no cell-write tool is available, fall back to file output mode and tell the user.

Read the full file on GitHub · 555 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. 4d ago First seen · 555 lines · 28 tokens per session scan B f810db85a95a

Subscribe to this mod's changes

dr-forecast-variance is a skill published in the GitHub repository Datarails/dr-claude-code-plugins-re (3 stars, last pushed 5d ago), licensed MIT. It adds 28 tokens to every session and 9,731 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (subtle steering). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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