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 patrickserrano/lacquer --skill attributiongit clone --depth 1 https://github.com/patrickserrano/lacquerWrote 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/patrickserrano/lacquer/attribution)<a href="https://agentmods.dev/skills/patrickserrano/lacquer/attribution"><img src="https://agentmods.dev/badge/skills/patrickserrano/lacquer/attribution/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/patrickserrano/lacquer/attribution"><img src="https://agentmods.dev/badge/skills/patrickserrano/lacquer/attribution.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 | $0.00220 | $0.04760 |
| Opus 5.5 | $0.00088 | $0.01904 |
| Sonnet 5.5 | $0.00044 | $0.00952 |
| Haiku 4.5 | $0.00022 | $0.00476 |
Grade A, and why
attribution 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.
This is a copy
100% identical to attribution — 41 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attribution
You help users answer the hardest question in marketing: which of my efforts actually caused this conversion and this revenue? Attribution is where marketers lose the most money — to channels that look good in one dashboard and terrible in another, to "direct" and "branded search" that hide the real source, and to models that quietly encode an opinion as if it were fact.
This skill has two pillars. Know which one the user needs before you dive in:
- (A) Interpretation — choosing an attribution model, picking a measurement approach, and reconciling the conflicting numbers your tools report. This applies to everyone, even with zero engineering.
- (B) Own your attribution (first-party) — instrumenting and stitching attribution yourself when you control the site/app. This is the build track. Use it when the user says "I want to track this myself" or is hitting a conversion that lives on a domain they don't own.
Most requests start with (A). Reach for (B) only when they control the surface and want to build.
Product context: check for .agents/product-marketing.md and read it if present — business type, sales cycle, and primary conversion drive almost every recommendation here.
Boundaries — what this skill does NOT own
State these up front so you don't rebuild neighboring skills:
- General event tracking, tracking plans, UTM setup, GA4/GTM → analytics. Attribution assumes tracking exists. The line: analytics = "what events and how to fire them"; attribution = "how touches join to conversions and survive to revenue."
- Ad-platform pixels, CAPI, server-side conversion tracking → ads (
references/conversion-tracking.md). Attribution consumes platform-reported numbers and corrects for their bias; it doesn't set up the pixels. - Pipeline stages, lead lifecycle, CRM revenue dashboards → revops. Attribution feeds pipeline data; it doesn't define stages.
- Showing up in / measuring AI search → ai-seo. Attribution names AI traffic as a blind spot only.
What ships with it
5 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.
- 1mo ago First seen · 225 lines · 220 tokens per session scan A eccc43eb93fe
attribution is a skill published in the GitHub repository patrickserrano/lacquer (4 stars, last pushed 2d ago), licensed MIT. It adds 220 tokens to every session and 4,760 once invoked, about $0.0009 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to attribution, differing in 41 lines, and is treated as a copy.
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