analytics-product-v2

analytics-product-v2 is a skill for Claude Code, Codex from diegosouzapw/awesome-omni-skills. It costs 79 tokens per session (4,037 once invoked), scanned A, original, MIT.

A workflow guide for product analytics: measuring how people use a product with tools such as PostHog and Mixpanel. It covers events, funnels, cohorts, retention, a main success metric, goals, and dashboards.

In plain words
What is it for?
Use it to define important product events, build funnels, study retention and cohorts, choose a main product metric, and create dashboards.
Why use it?
It helps turn product-usage data into decisions instead of leaving teams with disconnected events or reports.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex; mentions Gemini CLI; mentions OpenCode.

Good fit Use it to define important product events, build funnels, study retention and cohorts, choose a main product metric, and create dashboards.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/diegosouzapw/awesome-omni-skills/analytics-product-v2
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.

Any agent
npx skills add diegosouzapw/awesome-omni-skills --skill analytics-product-v2
Clone the repo
git clone --depth 1 https://github.com/diegosouzapw/awesome-omni-skills

Made for: Claude Code, Codex.

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 analytics-product-v2

README.md
[![agentmods](https://agentmods.dev/badge/skills/diegosouzapw/awesome-omni-skills/analytics-product-v2/github.svg)](https://agentmods.dev/skills/diegosouzapw/awesome-omni-skills/analytics-product-v2)
Your own site
<a href="https://agentmods.dev/skills/diegosouzapw/awesome-omni-skills/analytics-product-v2"><img src="https://agentmods.dev/badge/skills/diegosouzapw/awesome-omni-skills/analytics-product-v2/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 analytics-product-v2

Your own site · 80×15
<a href="https://agentmods.dev/skills/diegosouzapw/awesome-omni-skills/analytics-product-v2"><img src="https://agentmods.dev/badge/skills/diegosouzapw/awesome-omni-skills/analytics-product-v2.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,037 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00079 $0.04037
Opus 5 $0.00039 $0.02018
Sonnet 5 $0.00016 $0.00807
Haiku 4.5 $0.00008 $0.00404

Measured 8d ago against content hash a34a4a1bbf46, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

analytics-product-v2 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 8d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/analytics-product-v2/SKILL.md · 424 lines

How it starts

The opening of the file, as written. The whole thing — 424 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ANALYTICS-PRODUCT — Decida com Dados

Overview

This public intake copy packages plugins/antigravity-awesome-skills/skills/analytics-product from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

ANALYTICS-PRODUCT — Decida com Dados

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: How It Works, Analytics-Product — Decida Com Dados, Eventos Essenciais Da Auri, Implementacao Posthog (Python), Uso:, Funil De Ativacao Auri.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

  • When you need specialized assistance with this domain
  • The task is unrelated to analytics product
  • A simpler, more specific tool can handle the request
  • The user needs general-purpose assistance without domain expertise
  • Use when the request clearly matches the imported source intent: Analytics de produto — PostHog, Mixpanel, eventos, funnels, cohorts, retencao, north star metric, OKRs e dashboards de produto.
  • Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.

Operating Table

Situation Start here Why it matters
First-time use metadata.json Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review ORIGIN.md Gives reviewers a plain-language audit trail for the imported source
Workflow execution SKILL.md Starts with the smallest copied file that materially changes execution
Supporting context SKILL.md Adds the next most relevant copied source file without loading the entire package
Handoff decision ## Related Skills Helps the operator switch to a stronger native skill when the task drifts

Read the full file on GitHub · 424 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 8d ago First seen · 424 lines · 79 tokens per session scan A a34a4a1bbf46

Subscribe to this mod's changes

analytics-product-v2 is a skill published in the GitHub repository diegosouzapw/awesome-omni-skills (140 stars, last pushed 2mo ago), licensed MIT. It adds 79 tokens to every session and 4,037 once invoked, about $0.0004 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 2026-09-03.