impact-sizing

impact-sizing is a skill for Claude Code, Codex from ramybarsoum/prodkit. It costs 22 tokens per session (445 once invoked), scanned A, original, MIT.

A product-planning method for estimating the likely value of a feature. It uses impact drivers, confidence levels, and a four-step sizing process.

In plain words
What is it for?
Assessing user impact, revenue effects, problem severity, likely adoption, strategic fit, and the evidence behind a feature estimate.
Why use it?
It makes feature estimates more explicit by connecting them to user problems, business information, research, metrics, and strategy.

Skill for Claude CodeCodex

Part of the prodkit plugin — 10 skills 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/ramybarsoum/prodkit/impact-sizing
Any agent
npx skills add ramybarsoum/prodkit --skill impact-sizing
Clone the repo
git clone --depth 1 https://github.com/ramybarsoum/prodkit

Made for: Claude Code, Codex.

Or install prodkit, the plugin that ships this one along with the rest of its 10 skills.

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 impact-sizing

README.md
[![agentmods](https://agentmods.dev/badge/skills/ramybarsoum/prodkit/impact-sizing.svg)](https://agentmods.dev/skills/ramybarsoum/prodkit/impact-sizing)
Your own site
<a href="https://agentmods.dev/skills/ramybarsoum/prodkit/impact-sizing"><img src="https://agentmods.dev/badge/skills/ramybarsoum/prodkit/impact-sizing.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 445 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 $0.00022 $0.00445
Opus 5 $0.00011 $0.00222
Sonnet 5 $0.00004 $0.00089
Haiku 4.5 $0.00002 $0.00044

Measured 3d ago against content hash b4e730471377, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

impact-sizing 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 3d 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/impact-sizing/SKILL.md · 44 lines

How it starts

The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interaction style: Use the AskUserQuestion tool for all structured questions in this skill. Group related questions together (2-3 per call) rather than asking one at a time.

/impact-sizing - Quantify Feature Value

Systematically estimate the impact of a feature using the 4-step framework.

Context Routing Logic (Internal - for Claude)

Automatic Context Checks: When this skill is invoked, immediately check:

Source Files/Folders Search Terms What to Extract
Current PRD projects/*/ feature name from chat User impact, problem severity
User Research knowledge/research/*.md feature problem, user quotes Addressable users, pain severity
Business Model knowledge/company/business-info.md pricing, revenue model, TAM Revenue impact drivers
Historical Data knowledge/metrics/*.md similar features, baseline conversion Reference adoption rates
Strategy knowledge/strategy/*.md feature strategic fit Resource availability, priority context
Product Principles knowledge/company/product-principles.md product principles, core values Which principles this feature embodies and how

Context Priority:

  1. Product principles alignment FIRST
  2. Feature definition and user impact SECOND
  3. Business model and pricing THIRD
  4. User base size and addressable segment FOURTH
  5. Historical precedent for similar features FIFTH

Cross-Skill Links:

  • If sizing is unclear → Link to /impact-sizing (this skill)
  • If comparing options → Use this to inform /experiment-decision
  • If building business case → Reference in PRD and /write-prod-strategy
  • If identifying leading metrics → Connect to /feature-metrics and /metrics-framework

Read the full file on GitHub · 44 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. 3d ago First seen · 44 lines · 22 tokens per session scan A b4e730471377

Subscribe to this mod's changes

impact-sizing is a skill published in the GitHub repository ramybarsoum/prodkit (4 stars, last pushed 4mo ago), licensed MIT. It adds 22 tokens to every session and 445 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 2026-08-31.