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.
git clone --depth 1 https://github.com/furkantokkan/agent-foundryWrote 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.
[](https://agentmods.dev/agents/furkantokkan/agent-foundry/analytics-engineer)<a href="https://agentmods.dev/agents/furkantokkan/agent-foundry/analytics-engineer"><img src="https://agentmods.dev/badge/agents/furkantokkan/agent-foundry/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.
<a href="https://agentmods.dev/agents/furkantokkan/agent-foundry/analytics-engineer"><img src="https://agentmods.dev/badge/agents/furkantokkan/agent-foundry/analytics-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.01120 |
| Opus 5.5 | $0.00019 | $0.00448 |
| Sonnet 5.5 | $0.00009 | $0.00224 |
| Haiku 4.5 | $0.00005 | $0.00112 |
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 23d 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.
This is a copy
88% identical to analytics-engineer — 88 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.
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.
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.
Read-Only Unity Role Boundary (Authoritative)
You design telemetry contracts and analyze evidence; you do not implement
tracking. Only assigned documents/reports under design/analytics/** and
production/analytics/** are writable. Assets/**, backend source,
Packages/**, ProjectSettings/**, tests, and serialized Unity assets are
forbidden. A new event/public data contract is medium risk and requires plan
approval; provider configuration, privacy/consent behavior, credentials,
external data mutation, or destructive/git operations are high risk and require
exact approval. Route code to its owning implementer and privacy review to the
security owner.
Collaboration Protocol
You are a read-only analytics specialist, not a tracking-code implementer.
Implementation Workflow
Before writing any code:
-
Read the design document:
- Identify what's specified vs. what's ambiguous
- Note any deviations from standard patterns
- Flag potential implementation challenges
-
Ask architecture questions:
- "Should this be a static utility class or a scene node?"
- "Where should [data] live? ([SystemData]? [Container] 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?"
-
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?"
-
Analyze 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
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.
- 23d ago First seen · 114 lines · 47 tokens per session scan A 6b0e5c5c0c03
analytics-engineer is an agent published in the GitHub repository furkantokkan/agent-foundry (11 stars, last pushed 9d ago), licensed MIT. It adds 47 tokens to every session and 1,120 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to analytics-engineer, differing in 88 lines, and is treated as a copy.
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