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.
npx skills add hoatv2211/GameStudio-CodexKIT --skill product-analytics-experiment-reviewgit clone --depth 1 https://github.com/hoatv2211/GameStudio-CodexKITWrote 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/skills/hoatv2211/gamestudio-codexkit/product-analytics-experiment-review)<a href="https://agentmods.dev/skills/hoatv2211/gamestudio-codexkit/product-analytics-experiment-review"><img src="https://agentmods.dev/badge/skills/hoatv2211/gamestudio-codexkit/product-analytics-experiment-review/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/skills/hoatv2211/gamestudio-codexkit/product-analytics-experiment-review"><img src="https://agentmods.dev/badge/skills/hoatv2211/gamestudio-codexkit/product-analytics-experiment-review.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 | $0.00054 | $0.00845 |
| Opus 5 | $0.00027 | $0.00423 |
| Sonnet 5 | $0.00011 | $0.00169 |
| Haiku 4.5 | $0.00005 | $0.00085 |
Grade A, and why
product-analytics-experiment-review 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 10d 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
83% identical to audio-content-pipeline-review — 30 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Analytics Experiment Review
Overview
Provide an evidence-first contract for experiment hypothesis, population, assignment, metrics, guardrails, instrumentation, segmentation, sample size, significance, novelty, ethics, and decisions.
When to use
Use only for the trigger conditions in the description and when the requested artifact needs explicit owners, evidence, limitations, and verification.
When NOT to use
Do not use only to define telemetry event fields or to launch an experiment.
Required inputs and context discovery
Collect exact project and build identity, requested scope, owners, dependencies, constraints, existing evidence, commands, artifact paths, risks, approvals, rollback or recovery, and unavailable information.
Safety and risk level
Risk level is read-only. Read-only review never authorizes mutation. Any load, rollout, publication, service, database, credential, or external-system action requires explicit human approval and bounded stop conditions.
Workflow
- State the product decision, falsifiable hypothesis, unit of randomization, and population. Completion criterion: evidence is recorded and unresolved items are explicit.
- Define primary metric, guardrails, segments, attribution window, and instrumentation evidence. Completion criterion: evidence is recorded and unresolved items are explicit.
- Review sample size, power, duration, peeking, novelty, interference, and data quality. Completion criterion: evidence is recorded and unresolved items are explicit.
- Check player harm, fairness, privacy, rollback, and operational stop conditions. Completion criterion: evidence is recorded and unresolved items are explicit.
- Return approve, revise, reject, or BLOCKED with pre-registered decision rules. Completion criterion: evidence is recorded and unresolved items are explicit.
Evidence and output contract
Produce experiment-review.json with scope, snapshot, findings, owners, commands and exit codes, artifacts, acceptance criteria, Verified facts, Snapshot assumptions, Unverified hypotheses, BLOCKED items, and next actions.
What ships with it
1 file 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.
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.
- 10d ago First seen · 79 lines · 54 tokens per session scan A 136bca4cee5f
product-analytics-experiment-review is a skill published in the GitHub repository hoatv2211/GameStudio-CodexKIT (3 stars, last pushed 3d ago), licensed MIT. It adds 54 tokens to every session and 845 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to audio-content-pipeline-review, differing in 30 lines, and is treated as a copy.
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