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

Orchestration Logic

Command Routing

1. Parse the user's command to determine the sub-skill
2. If no sub-command given, ask which action they need
3. 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)

Niche Detection

Detect account niche from bio, content patterns, and hashtag analysis:

Adapt hook library selection, caption voice, CTA strategy, and content mix recommendations based on detected niche. If the user has configured references/account-baseline.md, use that data instead of detecting.

Algorithm Priority (2026)

Every piece of content is optimized in this priority order:

Quality Gates

Hard rules. Content that violates any gate is blocked from delivery:

Scoring Methodology

Content Quality Score (0-100)

5-category weighted scoring from references/scoring-system.md:

Scoring Bands

Content scoring below 80 MUST include specific revision instructions per deficient category. Do not just deliver the score.

Priority Levels (for audit findings)

• Critical: Content violates a Quality Gate (fix immediately)
• High: Score < 60, significant performance drag (fix before posting)
• Medium: Score 60-79, optimization opportunity (improve within week)
• Low: Minor polish, best practice (backlog)

Reference Files

Load on-demand as needed. NEVER load all references at startup.

Path resolution: All references at ~/.claude/skills/ig/references/. Sub-skills referencing references/*.md resolve to this path.

Sub-Skills

This skill orchestrates 13 specialized sub-skills:

Agents

For parallel analysis during /ig audit:

Agent Details

ig-content: Spawned as subagent during /ig audit. Reads recent posts, scores each against the 5-category rubric, identifies patterns in top/bottom performers. Outputs: per-post scores, category averages, content mix analysis.

ig-engagement: Analyzes engagement metrics from API data. Calculates save rates, DM-send rates, completion rates. Identifies which hook categories and content types drive the highest engagement. Outputs: engagement heatmap, best/worst performers by signal type.

ig-creative: Checks format compliance across recent posts. Validates safe zones, duration targets, thumbnail quality. Flags posts violating format-specs.md. Outputs: compliance checklist, violation list, format distribution.

ig-growth: Tracks follower growth rate, reach trends, posting frequency impact. Correlates posting schedule with performance. Outputs: growth metrics, optimal posting frequency and timing.

ig-competitor: Compares account metrics against niche benchmarks. Identifies content gaps (topics competitors cover that account doesn't). Spots trending formats and hook patterns. Outputs: competitive positioning, actionable gaps.

ig-compliance: Checks affiliate posts for proper disclosure, validates Quality Gate adherence across all recent content. Outputs: compliance report, violation flags with post references.

Execution Flow

Standard execution order for /ig reel:

1. Parse: Identify topic, detect content type and niche context
2. Load References: format-specs.md + hook-library.md + content-rules.md
3. Hook: Generate 3 hook variants from different categories, score each, select best
4. Script: Structure body (problem -> solution -> insight) with segment timing
5. Caption: Write 500+ char caption with save CTA and niche hashtags
6. Thumbnail: Describe thumbnail concept with text overlay
7. Score: Apply full 5-category Content Quality Score
8. Deliver: Output complete package with score and revision notes

For /ig analyze, steps 1-2 run, then API calls replace steps 3-7 with data analysis. For /ig audit, all 6 agents spawn in parallel, results aggregate into unified report.

Instagram API Integration

Graph API Authentication

Instagram data is accessed via the Facebook Graph API at https://graph.facebook.com/v21.0. Do NOT use graph.instagram.com (that endpoint rejects Page Tokens).

Two-Token System:

• User Token (INSTAGRAM_ACCESS_TOKEN): For ads, user-level queries
• Page Token (META_PAGE_TOKEN): Required for all Instagram content endpoints (media, insights, stories)

If META_PAGE_TOKEN is stale or missing, derive a fresh one:

source ~/Desktop/.env
PT=$(curl -s "https://graph.facebook.com/v21.0/$META_PAGE_ID?fields=access_token&access_token=$INSTAGRAM_ACCESS_TOKEN" \
  | python3 -c "import sys,json; print(json.load(sys.stdin)['access_token'])")

Environment variables (load with source ~/Desktop/.env):

• INSTAGRAM_ACCESS_TOKEN: Long-Lived User Token
• META_PAGE_TOKEN: Page Token (required for content endpoints)
• INSTAGRAM_BUSINESS_ACCOUNT_ID: IG Business Account ID
• META_PAGE_ID: Facebook Page ID (for token derivation)
• META_AD_ACCOUNT_ID: Ad Account ID (for ads endpoints)

Endpoints

Base URL: https://graph.facebook.com/v21.0
Auth: Page Token for content, User Token for ads
Rate Limit: 200 calls/hour per token

Content endpoints (Page Token):
  GET /{ig-id}?fields=id,username,media_count,followers_count,follows_count,biography,website,profile_picture_url
  GET /{ig-id}/media?fields=id,caption,media_type,thumbnail_url,timestamp,like_count,comments_count,permalink&limit=50
  GET /{media-id}/insights?metric=reach,saved,shares,likes,comments,total_interactions
  GET /{ig-id}/insights?metric=reach,follower_count,profile_views&period=day&since={unix}&until={unix}
  GET /{ig-id}/insights?metric=accounts_engaged,total_interactions&metric_type=total_value&period=day&since={unix}&until={unix}
  GET /{ig-id}/stories?fields=id,media_type,timestamp

IMPORTANT: Do NOT request impressions or plays (deprecated for Reels in v22+). accounts_engaged requires metric_type=total_value and cannot be mixed with time-series metrics.

Script Usage

The scripts/analyze_post.py script handles token management automatically:

source ~/Desktop/.env
python3 scripts/analyze_post.py --user-id $INSTAGRAM_BUSINESS_ACCOUNT_ID --token $INSTAGRAM_ACCESS_TOKEN --page-token $META_PAGE_TOKEN --page-id $META_PAGE_ID

If --page-token is omitted, the script derives one from --token + --page-id.

Graceful Degradation

If API access is not configured or token is expired:

1. Inform the user that live data is unavailable
2. Fall back to data in references/account-baseline.md (if populated)
3. Clearly mark any analysis as "based on cached data, not live"
4. Never fabricate metrics

Setup: Account Configuration

After installation, configure for your account:

1. Populate account-baseline.md with your account metrics:
   • Run /ig analyze to pull live data via API
   • Or manually enter: followers, avg engagement, top posts, posting schedule
2. Set API credentials in your .env file
3. Customize hook-library.md with hooks that work in your niche
4. Run /ig audit to establish your baseline scores

The skill works without configuration (using general best practices), but performs significantly better with account-specific data.

Anti-Patterns (Never Do These)