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 nicojunk/claude-ig --skill ig-affiliategit clone --depth 1 https://github.com/nicojunk/claude-igWrote 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/nicojunk/claude-ig/ig-affiliate)<a href="https://agentmods.dev/skills/nicojunk/claude-ig/ig-affiliate"><img src="https://agentmods.dev/badge/skills/nicojunk/claude-ig/ig-affiliate/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/nicojunk/claude-ig/ig-affiliate"><img src="https://agentmods.dev/badge/skills/nicojunk/claude-ig/ig-affiliate.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 | $0.00039 | $0.01483 |
| Opus 5.5 | $0.00016 | $0.00593 |
| Sonnet 5.5 | $0.00008 | $0.00297 |
| Haiku 4.5 | $0.00004 | $0.00148 |
Grade A, and why
ig-affiliate 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IG Affiliate -- Compliant affiliate content creation
Key references:
references/affiliate-compliance.md-- partner playbooks, disclosure rules, spacing constraintsreferences/format-specs.md-- format dimensions, duration limits, text sizingreferences/hook-library.md-- proven hook patterns with performance datareferences/scoring-system.md-- engagement scoring criteria and thresholds
Active Partners: Harvest Republic, Les Mills, InnoNature, Sunday Natural
Phase 1: Partner Selection
-
Load
references/affiliate-compliance.mdfor partner playbooks. -
Confirm which partner the content is for. If not specified, ask the user.
-
Load the partner-specific playbook section which includes:
- Product/service to promote
- Key selling points and approved claims
- Affiliate link or discount code
- Commission structure (for internal reference only, never share publicly)
- Content restrictions (what NOT to say)
- Past performance data (if available)
-
Verify the partner is on the active partners list. If not, flag to the user.
Phase 2: Content Type Selection
Select from 5 proven affiliate content patterns:
| Pattern | Format | Best For | Save Potential |
|---|---|---|---|
| Honest Review | Reel (60-90s) | Trust building, high conversion | Medium |
| Day-in-the-Life Integration | Reel (30-60s) | Natural placement, low resistance | Low |
| Problem-Solution | Carousel (7-10 slides) | Educational angle, high save rate | High |
| Before/After or Comparison | Carousel (5-7 slides) | Visual proof, social proof | Medium |
| Quick Tip with Product | Reel (15-30s) | Easy production, high reach | Low |
Selection criteria:
- Match the pattern to the product type
- Consider recent content mix (avoid 2 reviews in a row)
- Prioritize patterns with higher save potential for long-term value
- Consider the user's production capacity
Document the selected pattern and reasoning.
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 · 191 lines · 39 tokens per session scan A d90427581a30
ig-affiliate is a skill published in the GitHub repository nicojunk/claude-ig (23 stars, last pushed 2mo ago), licensed MIT. It adds 39 tokens to every session and 1,483 once invoked, about $0.0002 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.
ig-affiliate compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ig-affiliatenicojunk/claude-ig | Skill | 23 | 2mo ago | MIT | A | 39 | Claude Code |
| 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 |