feature-breakdown

feature-breakdown is a command for coding agents from AInsteinsBR/renata. It costs 18 tokens per session (1,344 once invoked), scanned A, original, MIT.

A command that turns a product requirements document into a ranked list of three to seven possible features and identifies the main feature. A product requirements document describes what a product should do and why.

In plain words
What is it for?
Use it during product planning to classify features as required or out of scope, estimate effort, connect them to hypotheses, and decide what to build first.
Why use it?
It helps turn broad product ideas into a smaller, ordered set of features tied to user needs and assumptions.

Command

Part of the renata plugin — 3 skills, 33 commands, 6 agents, 2 hooks 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 commands/ainsteinsbr/renata/feature-breakdown
Clone the repo
git clone --depth 1 https://github.com/AInsteinsBR/renata

Or install renata, the plugin that ships this one along with the rest of its 3 skills, 33 commands, 6 agents, 2 hooks.

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 feature-breakdown

README.md
[![agentmods](https://agentmods.dev/badge/commands/ainsteinsbr/renata/feature-breakdown.svg)](https://agentmods.dev/commands/ainsteinsbr/renata/feature-breakdown)
Your own site
<a href="https://agentmods.dev/commands/ainsteinsbr/renata/feature-breakdown"><img src="https://agentmods.dev/badge/commands/ainsteinsbr/renata/feature-breakdown.svg" alt="Measured on agentmods" height="20"></a>
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,344 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 $0.00018 $0.01344
Opus 5 $0.00009 $0.00672
Sonnet 5 $0.00004 $0.00269
Haiku 4.5 $0.00002 $0.00134

Measured 5d ago against content hash f30440996c56, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

feature-breakdown 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 5d 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.

commands/feature-breakdown.md · 114 lines

How it starts

The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/renata:feature-breakdown — List candidate features and mark the anchor

You are a tech lead + PM. Given a product/PRD, you generate a prioritized list of 3-7 candidate features, with the anchor feature marked.

Respond to the user and generate document content in the user's language (the language they are writing in).

Before generating

  1. Read @docs/prd/ (an active PRD is required).

  2. Read @docs/business-context/ (personas + journey).

  3. If a PRD or persona is missing, instruct to run /renata:prd or /renata:persona first and abort.

  4. Ask ONE at a time:

    • Which high-level capabilities do you imagine for this product? (3-7 items)
    • For each one: binary categoryMUST (without it, some PRD hypothesis falls) or OUT-OF-SCOPE (does not enter the product, goes to anti-features). No intermediate categories. The category stays binary — the value axis below serves to order the MUSTs among themselves, not to create a "half-MUST".
    • For each MUST: estimated effort (XS/S/M/L/XL) and entry phase.
    • For each MUST: which hypothesis it addresses (H1, H2…) + learning value (High/Medium/Low) — how much does this feature, if delivered, tell you about that hypothesis? If the PRD has N hypotheses, different features may prove different hypotheses — mark which one. A feature that proves/disproves a bet is worth more early than a feature that just completes the product.
    • Dependencies between them?

How to choose the anchor feature

Apply the 5 canonical criteria:

  1. MUST without a doubt — without it, a PRD hypothesis cannot be validated.
  2. Others depend on it — high out-degree in the graph.
  3. Fits in P (1-2 phases) — not monstrous. If it's XL, break it down.
  4. Isolated value — even alone, it proves something about the hypothesis.
  5. Kills the biggest hypothesis risk first — among the candidates that pass 1-4, prefer the one with the highest learning value. The anchor is not just the topological root of the graph; it is the one that gives /renata:hypothesis-check something to measure as soon as possible.

Read the full file on GitHub · 114 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. 5d ago First seen · 114 lines · 18 tokens per session scan A f30440996c56

Subscribe to this mod's changes

feature-breakdown is a command published in the GitHub repository AInsteinsBR/renata (10 stars, last pushed 14d ago), licensed MIT. It adds 18 tokens to every session and 1,344 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.