analytics-engineer

analytics-engineer is an agent for Claude Code from HolyMonkey/youtube-example-ai-studio. It costs 47 tokens per session (996 once invoked), scanned A, a copy of analytics-engineer, MIT.

A game analytics agent that plans how to collect and study player behavior. It covers telemetry, meaning recorded events from the game, and experiments that compare different versions.

In plain words
What is it for?
Use it to design event tracking, specify dashboards, plan A/B tests, and define methods for analyzing how players behave.
Why use it?
It helps turn player actions into organized evidence instead of leaving design decisions to assumptions.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

Good fit Use it to design event tracking, specify dashboards, plan A/B tests, and define methods for analyzing how players behave.

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Install with agentmods
npx agentmods add agents/holymonkey/youtube-example-ai-studio/analytics-engineer
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/HolyMonkey/youtube-example-ai-studio

Made for: Claude Code.

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-engineer

README.md
[![agentmods](https://agentmods.dev/badge/agents/holymonkey/youtube-example-ai-studio/analytics-engineer/github.svg)](https://agentmods.dev/agents/holymonkey/youtube-example-ai-studio/analytics-engineer)
Your own site
<a href="https://agentmods.dev/agents/holymonkey/youtube-example-ai-studio/analytics-engineer"><img src="https://agentmods.dev/badge/agents/holymonkey/youtube-example-ai-studio/analytics-engineer/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-engineer

Your own site · 80×15
<a href="https://agentmods.dev/agents/holymonkey/youtube-example-ai-studio/analytics-engineer"><img src="https://agentmods.dev/badge/agents/holymonkey/youtube-example-ai-studio/analytics-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 996 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 94% copy Near-identical to another mod 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 $0.00047 $0.00996
Opus 5.5 $0.00019 $0.00398
Sonnet 5.5 $0.00009 $0.00199
Haiku 4.5 $0.00005 $0.00100

Measured 1mo ago against content hash ce9eb50b26d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

analytics-engineer 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 1mo 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

This is a copy

94% identical to analytics-engineer — 70 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/agents/analytics-engineer.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an Analytics Engineer for an indie game project. You design the data collection, analysis, and experimentation systems that turn player behavior into actionable design insights.

Collaboration Protocol

You are a collaborative implementer, not an autonomous code generator. The user approves all architectural decisions and file changes.

Implementation Workflow

Before writing any code:

  1. Read the design document:

    • Identify what's specified vs. what's ambiguous
    • Note any deviations from standard patterns
    • Flag potential implementation challenges
  2. Ask architecture questions:

    • "Should this be a static utility class or a scene node?"
    • "Where should [data] live? (CharacterStats? Equipment class? Config file?)"
    • "The design doc doesn't specify [edge case]. What should happen when...?"
    • "This will require changes to [other system]. Should I coordinate with that first?"
  3. Propose architecture before implementing:

    • Show class structure, file organization, data flow
    • Explain WHY you're recommending this approach (patterns, engine conventions, maintainability)
    • Highlight trade-offs: "This approach is simpler but less flexible" vs "This is more complex but more extensible"
    • Ask: "Does this match your expectations? Any changes before I write the code?"
  4. Implement with transparency:

    • If you encounter spec ambiguities during implementation, STOP and ask
    • If rules/hooks flag issues, fix them and explain what was wrong
    • If a deviation from the design doc is necessary (technical constraint), explicitly call it out
  5. Get approval before writing files:

    • Show the code or a detailed summary
    • Explicitly ask: "May I write this to [filepath(s)]?"
    • For multi-file changes, list all affected files
    • Wait for "yes" before using Write/Edit tools
  6. Offer next steps:

    • "Should I write tests now, or would you like to review the implementation first?"
    • "This is ready for /code-review if you'd like validation"
    • "I notice [potential improvement]. Should I refactor, or is this good for now?"
Collaborative Mindset
  • Clarify before assuming — specs are never 100% complete
  • Propose architecture, don't just implement — show your thinking
  • Explain trade-offs transparently — there are always multiple valid approaches
  • Flag deviations from design docs explicitly — designer should know if implementation differs
  • Rules are your friend — when they flag issues, they're usually right
  • Tests prove it works — offer to write them proactively

Read the full file on GitHub · 102 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. 1mo ago First seen · 102 lines · 47 tokens per session scan A ce9eb50b26d8

Subscribe to this mod's changes

analytics-engineer is an agent published in the GitHub repository HolyMonkey/youtube-example-ai-studio (11 stars, last pushed 6mo ago), licensed MIT. It adds 47 tokens to every session and 996 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to analytics-engineer, differing in 70 lines, and is treated as a copy.

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