Agent skill

Impact Quantification

by nimrodfisher in nimrodfisher/data-analytics-skills

Estimate and communicate business impact of insights. An agent skill from nimrodfisher/data-analytics-skills.

MITAuto-check passed

Install Impact Quantification

skills CLI
$ npx skills add nimrodfisher/data-analytics-skills --skill impact-quantification -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install nimrodfisher/data-analytics-skills impact-quantification --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/05-stakeholder-communication/impact-quantification .claude/skills/impact-quantification && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
impact-quantification
GitHub stars
465
Token cost
~502 tokens
SKILL.md length
209 words
Files
8 (incl. scripts, references, assets)
Skills in repo
31
Repo updated
First seen
Licence
MIT

At a glance

Estimate and communicate business impact of insights. An agent skill from nimrodfisher/data-analytics-skills.

  • Works in 6 steps: Classify the impact type — revenue… → Gather inputs — collect baseline… → Build the point estimate — use… → …
  • Sizing opportunities discovered in analysis
  • Runs Python scripts from its folder
  • Calculating ROI of recommended actions

What it does

Impact Quantification is an agent skill from nimrodfisher/data-analytics-skills. Estimate and communicate business impact of insights. Use when sizing opportunities discovered in analysis, calculating ROI of recommended actions, or prioritizing initiatives by potential impact.

Its SKILL.md is about 500 tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/business_case_template.md`, `assets/impact_estimate_template.md` and `references/assumption_documentation.md`).

The repository describes itself as: A comprehensive list of Claude & Codex skills for a wide range of data analytics tasks. The licence is MIT.

When your agent uses it

  • Sizing opportunities discovered in analysis
  • Calculating ROI of recommended actions
  • Prioritizing initiatives by potential impact

Example prompts

  • “/impact-quantification”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Classify the impact type — revenue growth, cost reduction, risk reduction, or efficiency gain. Each type has a different formula family…
  2. Gather inputs — collect baseline metrics, affected population size, expected lift/reduction, time horizon, and confidence level.
  3. Build the point estimate — use scripts/revenue_impact.py for revenue/growth scenarios or scripts/cost_savings.py for cost/efficiency…
  4. Add uncertainty bounds — use scripts/confidence_interval.py to produce low/base/high estimates. Never deliver a single number without a…
  5. Document assumptions — fill in references/assumption_documentation.md for every input that is estimated rather than directly measured…
  6. Package the estimate — complete assets/impact_estimate_template.md with the range, assumptions, confidence, and recommended action…

What it can do on your machine

Read from SKILL.md and the folder at commit 9449d36. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Impact Quantification loads about 502 tokens when it runs, and up to ~2k if it reads all its reference files. Until then it costs about 55 tokens; SKILL.md has 209 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~55
When it runs · the whole SKILL.md, loaded when a task matches
~502
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from nimrodfisher/data-analytics-skills at commit 9449d36, republished under its MIT licence (© nimrodfisher). 209 words, ~502 tokens.

Download SKILL.mdSave it as .claude/skills/impact-quantification/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
impact-quantification
description
Estimate and communicate business impact of insights. Use when sizing opportunities discovered in analysis, calculating ROI of recommended actions, or prioritizing initiatives by potential impact.

When to use

After an analytical finding surfaces a potential action, change, or opportunity. Use to produce a defensible numeric estimate that stakeholders can act on. Also use when prioritizing a backlog of initiatives — quantified impact is the primary ranking signal.

Process

  1. Classify the impact type — revenue growth, cost reduction, risk reduction, or efficiency gain. Each type has a different formula family (see references/impact_quantification_framework.md).
  2. Gather inputs — collect baseline metrics, affected population size, expected lift/reduction, time horizon, and confidence level.
  3. Build the point estimate — use scripts/revenue_impact.py for revenue/growth scenarios or scripts/cost_savings.py for cost/efficiency scenarios.
  4. Add uncertainty bounds — use scripts/confidence_interval.py to produce low/base/high estimates. Never deliver a single number without a range.
  5. Document assumptions — fill in references/assumption_documentation.md for every input that is estimated rather than directly measured; note the sensitivity of the output to each.
  6. Package the estimate — complete assets/impact_estimate_template.md with the range, assumptions, confidence, and recommended action; optionally build the full assets/business_case_template.md for larger decisions.

Inputs the skill needs

  • Baseline metric value (current state)
  • Affected population or volume
  • Expected change (lift %, absolute, or rate change)
  • Time horizon (monthly / annual)
  • Confidence level in inputs (high / medium / low)

Output

  • Impact estimate with low/base/high range
  • Assumption log (source and sensitivity for each input)
  • Completed impact_estimate_template.md or business_case_template.md

© nimrodfisher, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references, assets) in 05-stakeholder-communication/impact-quantification of nimrodfisher/data-analytics-skills.

  • SKILL.md
  • assets/business_case_template.md
  • assets/impact_estimate_template.md
  • references/assumption_documentation.md
  • references/impact_quantification_framework.md
  • scripts/confidence_interval.py
  • scripts/cost_savings.py
  • scripts/revenue_impact.py

Open the folder on GitHubat commit 9449d36

Compare with similar skills

Impact Quantification next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Impact Quantification compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Impact Quantification this skillnimrodfisher/data-analytics-skills465—~502Automated safety check: PassMIT
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Natural Japanese Business Writingcoji/natural-japanese1.9k—~2.1kAutomated safety check: PassMIT
Open Editveedstudio/open-edit1.6k—~1.8kAutomated safety check: PassApache-2.0
Pitchcraft Persuasive Briefingsmoshuying/pitchcraft1911 repos~2.4kAutomated safety check: PassApache-2.0
My Weekly Reportmeain/dotfiles285—~2.5kAutomated safety check: PassMIT

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Questions about Impact Quantification

What does Impact Quantification do?

Estimate and communicate business impact of insights. An agent skill from nimrodfisher/data-analytics-skills. Impact Quantification is an agent skill from nimrodfisher/data-analytics-skills. Estimate and communicate business impact of insights.

When should I use Impact Quantification?

Impact Quantification fits situations like: sizing opportunities discovered in analysis; calculating ROI of recommended actions; prioritizing initiatives by potential impact.

How do I install Impact Quantification in Claude Code?

Run `npx skills add nimrodfisher/data-analytics-skills --skill impact-quantification -a claude-code`. Or copy the skill folder (05-stakeholder-communication/impact-quantification in nimrodfisher/data-analytics-skills) into .claude/skills/impact-quantification in your project. Claude Code loads it when a task matches its description.

How do I install Impact Quantification in Codex?

Run `npx skills add nimrodfisher/data-analytics-skills --skill impact-quantification -a codex`. Or copy the skill folder (05-stakeholder-communication/impact-quantification in nimrodfisher/data-analytics-skills) into .agents/skills/impact-quantification in your project. Codex loads it when a task matches its description.

Can I use Impact Quantification in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add nimrodfisher/data-analytics-skills --skill impact-quantification -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/impact-quantification, .gemini/skills/impact-quantification, .github/skills/impact-quantification and .opencode/skills/impact-quantification in your project.

What does Impact Quantification need to run?

Going by SKILL.md and its folder, Impact Quantification needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Impact Quantification access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Impact Quantification safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Impact Quantification use?

Impact Quantification is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Impact Quantification use?

About 502 tokens (SKILL.md is roughly 2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.5k tokens, read only when the agent opens those files.

What are the alternatives to Impact Quantification?

Skills that share tags, products or a category with Impact Quantification: Internal Communications Writer (anthropics/skills, 180k stars), Natural Japanese Business Writing (coji/natural-japanese, 1.9k stars), Open Edit (veedstudio/open-edit, 1.6k stars) and Pitchcraft Persuasive Briefings (moshuying/pitchcraft, 191 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Impact Quantification?

nimrodfisher (a GitHub user) maintains it in nimrodfisher/data-analytics-skills, which has 465 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on September 25, 2026.

Source: nimrodfisher/data-analytics-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.