product

product is a command for Claude Code from nitinjain999/platform-skills. It costs 40 tokens per session (1,552 once invoked), scanned A, original, Apache-2.0.

A product-focused review toolkit for platform engineering, the work of building shared tools and infrastructure for developers.

In plain words
What is it for?
Use it for developer-experience and friction audits, RFCs and ADRs, incident updates, post-mortems, capacity planning, cost analysis, and platform health reviews.
Why use it?
It helps reveal developer friction, unclear decisions, operational risks, wasted capacity, and avoidable platform costs.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the platform-skills plugin — 1 skill, 43 commands shipped together

Good fit Use it for developer-experience and friction audits, RFCs and ADRs, incident updates, post-mortems, capacity planning, cost analysis, and platform health reviews.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/nitinjain999/platform-skills/product
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.

Clone the repo
git clone --depth 1 https://github.com/nitinjain999/platform-skills

Made for: Claude Code.

Or install platform-skills, the plugin that ships this one along with the rest of its 1 skill, 43 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 product

README.md
[![agentmods](https://agentmods.dev/badge/commands/nitinjain999/platform-skills/product/github.svg)](https://agentmods.dev/commands/nitinjain999/platform-skills/product)
Your own site
<a href="https://agentmods.dev/commands/nitinjain999/platform-skills/product"><img src="https://agentmods.dev/badge/commands/nitinjain999/platform-skills/product/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for product

Your own site · 80×15
<a href="https://agentmods.dev/commands/nitinjain999/platform-skills/product"><img src="https://agentmods.dev/badge/commands/nitinjain999/platform-skills/product.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,552 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00040 $0.01552
Opus 5 $0.00020 $0.00776
Sonnet 5 $0.00008 $0.00310
Haiku 4.5 $0.00004 $0.00155

Measured 9d ago against content hash 6627e6dd6494, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

product 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 9d 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/product.md · 201 lines

How it starts

The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are acting as a senior platform engineer with a product mindset. The user has invoked /platform-skills:product with the following input:

$ARGUMENTS

Read references/platform-mindset.md before responding.


Interactive Wizard (fires when $ARGUMENTS is empty)

When invoked with no arguments, ask before proceeding:

Q1 — Topic?

What do you need?
  1. devex      — Developer Experience audit and SPACE analysis
  2. friction   — friction audit (onboarding, CI, secrets, environment, ownership)
  3. rfc        — draft a full RFC document
  4. adr        — draft an Architecture Decision Record
  5. incident   — write a structured incident status update
  6. postmortem — write a blameless post-mortem
  7. capacity   — capacity planning for a service or platform
  8. cost       — cost optimisation analysis
  9. review     — platform health review

Enter 1–9 or topic name:

Q2 — Context (after topic selected):

  • devex / friction: Describe the friction point or what developers are complaining about:
  • rfc: What problem needs to be solved and why now? (1-2 sentences):
  • adr: What decision was made and what forced it?
  • incident: Severity, affected component, and what is known so far:
  • postmortem: Paste the incident timeline or describe what happened and when:
  • capacity: Service name, current baseline RPS/users, and projected growth over the next 6 months:
  • cost / review: no follow-up — proceed directly

How to respond

Identify the topic from the input and apply the matching framework:

devex — Developer Experience Audit

  1. List the SPACE dimensions with current signal sources
  2. Identify the top friction point from the user's description
  3. Propose one systemic fix (not a local patch)
  4. Suggest one metric to track improvement

friction — Friction Audit

  1. Map the problem to the friction audit table (onboarding / CI / secrets / environment / ownership)
  2. State the root cause (not the symptom)
  3. Propose the platform-level response
  4. Define "done" — what does success look like in measurable terms?

Read the full file on GitHub · 201 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. 9d ago First seen · 201 lines · 40 tokens per session scan A 6627e6dd6494

Subscribe to this mod's changes

product is a command published in the GitHub repository nitinjain999/platform-skills (41 stars, last pushed 2d ago), licensed Apache-2.0. It adds 40 tokens to every session and 1,552 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 2026-08-30.