Instagram Content Benchmark

Follow shared public skill rules in:

• postplus-shared public skill rules

Use this skill when the user wants to:

• find strong Instagram post or Reel examples
• benchmark competitor content
• identify repeatable hooks, caption structures, or format patterns
• decide what type of Instagram content to recreate or adapt

Read these references before implementation:

• skills/20-research/instagram-references/actor-selection.md
• skills/20-research/instagram-references/normalized-schema.md
• skills/20-research/instagram-references/tool-contracts.md

Primary Hosted Collection Keys

• instagram-posts
• instagram-hashtags

Recommended Workflow

1. define seeds:
   • usernames
   • post URLs
   • Reel URLs
   • hashtags
2. scrape the first candidate pool at 10-15 posts or reels per theme
3. normalize posts and Reel-like results into one comparable dataset
4. rank by engagement, relevance, recency, and format fit
5. produce a shortlist of benchmark content
6. summarize:
   • repeated hooks
   • repeated visual formats
   • caption patterns
   • hashtag usage

Cost Discipline

Start with:

• 10-15 posts or reels per theme for the first pass
• one or two themes at a time
• comments only after a shortlist exists

Treat 10-15 posts or reels per theme as the first-pass boundary, not a preference. Do not ask the user to choose a broad crawl range up front and do not compile a wider first actor input from broad wording like "as many as possible" or "scan the whole niche." Expand only after the first shortlist proves seed quality and the user approves a second pass.

Public Skill Execution Contract

• keep benchmark briefs, actor inputs, raw datasets, normalized datasets, and shortlist caches under <work-folder>/.postplus/instagram-benchmark/
• keep only final user-facing summaries or shortlist exports outside .postplus/
• compile a small benchmark brief before the expensive collection step
• if PostPlus Cloud service is unavailable, unauthorized, or returns a stable network error, stop immediately instead of switching to ad hoc shell glue

Good Output

Return:

• top benchmark shortlist
• content-type split:
  • Reel
  • static post
  • carousel
• repeated opening patterns
• repeated value promises
• likely content pillars
• recommended next posts to inspect deeper

Handoff

Escalate to instagram-audience-voice when:

• the user wants to read comment sentiment and language

Escalate to video or creative analysis workflows outside this skill family when:

• the user wants shot-level breakdowns of the actual videos

Escalate to instagram-creator-discovery when:

• the user wants to turn benchmark content into a creator pool