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 tushaarmehtaa/tushar-skills --skill analyticsgit clone --depth 1 https://github.com/tushaarmehtaa/tushar-skillsWrote 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/tushaarmehtaa/tushar-skills/analytics)<a href="https://agentmods.dev/skills/tushaarmehtaa/tushar-skills/analytics"><img src="https://agentmods.dev/badge/skills/tushaarmehtaa/tushar-skills/analytics/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/tushaarmehtaa/tushar-skills/analytics"><img src="https://agentmods.dev/badge/skills/tushaarmehtaa/tushar-skills/analytics.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 | $0.00037 | $0.00928 |
| Opus 5 | $0.00018 | $0.00464 |
| Sonnet 5 | $0.00007 | $0.00186 |
| Haiku 4.5 | $0.00004 | $0.00093 |
Grade A, and why
analytics 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.
How it starts
The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analytics
Build the smallest measurement system that answers explicit product or operational questions. Preserve existing providers and schemas unless a migration is part of the request.
Workflow
- Inspect the framework, router/runtime, deployment target, auth model, existing analytics and monitoring packages, environment-variable examples, privacy controls, and current event calls.
- Define the decisions the data must support: acquisition, activation, retention, adoption, revenue, reliability, or incident response. For every metric, record its unit, eligible population and exclusions, numerator/event, denominator, cohort anchor where relevant, observation window, maturity/censoring rule, timezone, owner, and decision threshold. Record event names, required properties, identity rules, retention needs, and sensitive fields to exclude.
- Separate four concerns before choosing tools:
- traffic analytics;
- product analytics and experimentation;
- errors, traces, and logs;
- liveness, readiness, and business reporting.
- Reuse an installed provider. If none exists, recommend the minimum stack and explain the tradeoff. Ask only for unresolved choices that materially affect implementation, such as consent requirements, data residency, provider preference, or whether a database dependency belongs in readiness checks. Never ask the user to paste secrets into chat; scaffold names in
.env.exampleand let the user set values in the deployment environment. - Create or update a measurement plan before adding calls. Use stable event names, typed properties, server-side capture for authoritative outcomes, and a documented anonymous-to-authenticated identity transition.
- Implement only the selected paths:
- Read PostHog before changing PostHog browser/server setup, identity, page views, or events.
- Read Sentry before changing Sentry initialization, boundaries, logging, replay, tracing, or source maps.
- Read health endpoints before adding liveness/readiness routes or uptime monitoring.
- When an internal dashboard is requested, implement it as an authenticated product surface, not a public health endpoint. Use server-owned aggregate queries; define freshness and caching; reconcile each tile to its metric contract; enforce role/tenant access; suppress or coarsen small sensitive groups; and cover loading, empty, stale, partial, and error states. Keep operational status separate from product metrics even when they share a page.
- Apply privacy controls before capture: minimize properties, exclude credentials/payment data/content by default, avoid URLs or query strings that contain personal data, honor applicable consent/opt-out rules, and review replay masking and log scrubbing.
- Preserve secrets and deployment boundaries. Public ingestion tokens may be exposed only when the provider defines them as public; source-map tokens, service-role keys, and personal API keys stay server-side and out of logs and git.
What ships with it
3 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.
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.
- 9d ago First seen · 54 lines · 37 tokens per session scan A a2c28053fe16
analytics is a skill published in the GitHub repository tushaarmehtaa/tushar-skills (11 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 928 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.
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