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 krillinai/growth-skills --skill attribution-analysisgit clone --depth 1 https://github.com/krillinai/growth-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/krillinai/growth-skills/attribution-analysis)<a href="https://agentmods.dev/skills/krillinai/growth-skills/attribution-analysis"><img src="https://agentmods.dev/badge/skills/krillinai/growth-skills/attribution-analysis/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/krillinai/growth-skills/attribution-analysis"><img src="https://agentmods.dev/badge/skills/krillinai/growth-skills/attribution-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00034 | $0.02992 |
| Opus 5.5 | $0.00014 | $0.01197 |
| Sonnet 5.5 | $0.00007 | $0.00598 |
| Haiku 4.5 | $0.00003 | $0.00299 |
Grade A, and why
attribution-analysis 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 2mo 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attribution & Marketing Mix
Integrated Capabilities
This Skill consolidates adjacent workflows behind one trigger. Use the main workflow for core requests. When a request matches a module below, read that module before executing it:
Assign operational credit under explicit rules, reconcile it to observed customer and business outcomes, and expose how identity, windows, sources, models, and missing evidence change the result. Attribution describes a journey or allocates credit; it does not prove what caused growth or what would disappear if a channel stopped.
Read attribution-contract.md before accepting source, touchpoint, identity, conversion, customer, revenue, or attribution evidence. Read models-and-journeys.md before choosing or comparing first-touch, last-touch, multi-touch, platform, partner, MMP, B2B, account, app, or cross-device views. Read reconciliation-and-quality.md before combining platforms, product analytics, CRM, billing, finance, refunds, costs, or downstream value. Read causal-boundaries-and-governance.md before making incrementality, predictive-model, privacy, automation, or market-transfer claims. Read output-contract.md before delivery. Use playbook-sources.md to cite the pinned Growth Playbook basis.
Select One Mode
| Mode | Use |
|---|---|
audit |
Diagnose an existing attribution report, model, journey, source rule, platform claim, quality problem, or decision |
design |
Define a decision-specific attribution contract, journey views, model rules, validation, governance, and implementation handoff |
reconcile |
Resolve incompatible counts, entities, windows, systems, revenue states, overlap, unknowns, and downstream outcomes |
What ships with it
6 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.
- 2mo ago First seen · 137 lines · 34 tokens per session scan A 47e1e8e18736
attribution-analysis is a skill published in the GitHub repository krillinai/growth-skills (43 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 2,992 once invoked, about $0.0001 per session on Opus 5.5. 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.
attribution-analysis compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| attribution-analysiskrillinai/growth-skills | Skill | 43 | 2mo ago | MIT | A | 34 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |