Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/nicojunk/claude-ignpx agentmods add skills/nicojunk/claude-ig/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)<a href="https://agentmods.dev/skills/nicojunk/claude-ig/ig"><img src="https://agentmods.dev/badge/skills/nicojunk/claude-ig/ig.svg" alt="Measured on agentmods" 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 | $0.00201 | $0.04307 |
| Opus 5 | $0.00101 | $0.02153 |
| Sonnet 5 | $0.00040 | $0.00861 |
| Haiku 4.5 | $0.00020 | $0.00431 |
Grade A, and why
ig scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
PT=$(curl -s "https://graph.facebook.com/v21.0/$META_PAGE_ID?fields=access_token&access_token=$INSTAGRAM_ACCESS_TOKEN" \ How it starts
The opening of the file, as written. The whole thing — 350 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IG: Instagram Content Engine
Full-lifecycle Instagram management: hooks, Reels, Stories, Carousels, captions, affiliate content, performance analysis, competitor research, editorial planning, and content repurposing. Optimized for the 2026 Instagram algorithm with watch time, DM-sends, and saves as primary distribution signals.
Works for any Instagram account and niche. Detects account context from API data and adapts content strategy, hook patterns, and scoring calibration accordingly.
Quick Reference
| Command | What it does |
|---|---|
/ig reel <topic> |
Write a complete Reel (hook, script, caption, thumbnail) |
/ig hook <topic> |
Generate and score hooks for any format |
/ig caption <topic> |
Write an optimized caption (500+ chars, save CTA) |
/ig story <topic> |
Plan a Story sequence (slides, stickers, polls) |
/ig carousel <topic> |
Plan a Carousel (cover hook, slides, CTA) |
/ig analyze [post-url] |
Analyze post performance via Instagram API |
/ig audit |
Full content audit with parallel subagent delegation |
/ig competitor <accounts> |
Research competitor content |
/ig calendar [weekly|monthly] |
Generate an editorial content calendar |
/ig strategy |
Content strategy and positioning analysis |
/ig affiliate <partner> |
Create compliant affiliate content |
/ig comment |
Comment response strategy and automation |
/ig repurpose <post> |
Repurpose IG content for other platforms |
Orchestration Logic
Command Routing
- Parse the user's command to determine the sub-skill
- If no sub-command given, ask which action they need
- Route to the appropriate sub-skill:
reel/skript/video->ig-reel(full Reel production)hook/opening->ig-hook(hook generation and scoring)caption/beschreibung/text->ig-caption(caption writing)story/stories->ig-story(Story sequence planning)carousel/karussell/slides->ig-carousel(Carousel planning)analyze/analyse/performance/insights->ig-analyze(API-driven analysis)audit/check/health->ig-audit(full content audit with subagents)competitor/konkurrenz/research/spy->ig-competitor(competitor research)calendar/plan/kalender/schedule->ig-calendar(editorial calendar)strategy/strategie/positioning->ig-strategy(positioning and content mix)affiliate/werbung/kooperation/sponsored->ig-affiliate(compliant partner content)comment/kommentar/replies->ig-comment(comment response)repurpose/redistribute/cross-post->ig-repurpose(cross-platform repurposing)
What ships with it
12 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.
- references/account-baseline.md 27 KB
- references/affiliate-compliance.md 23 KB
- references/algorithm-2026.md 13 KB
- references/comment-responder.md 8.7 KB
- references/competitor-framework.md 40 KB
- references/content-rules.md 8.3 KB
- references/conversion-pipeline.md 8.0 KB
- references/format-specs.md 31 KB
- references/hook-library.md 40 KB
- references/repurpose-playbook.md 10 KB
- references/scoring-system.md 10.0 KB
- references/story-strategy.md 10 KB
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.
- 6d ago First seen · 350 lines · 201 tokens per session scan A 8674c6ad22f4
ig is a skill published in the GitHub repository nicojunk/claude-ig (11 stars, last pushed 6mo ago), licensed MIT. It adds 201 tokens to every session and 4,307 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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