instagram-content-benchmark
Benchmark Instagram posts and Reels to discover winning content patterns, shortlist high-value examples, and extract reusable hooks and formats.
- Installs
- 525
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/postplusai/postplus-skills --skill instagram-content-benchmark- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads instagram-content-benchmark automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Instagram Content Benchmark
Use this skill to benchmark Instagram posts and Reels, find strong examples, and extract reusable hooks, caption structures, formats, and content pillars.
Apply shared rulebook and user-guidance rules from postplus-shared.
Do Not Use When
- The user wants to evaluate known accounts. Route to
instagram-account-research. - The user wants to discover creators for outreach. Route to
instagram-creator-discovery. - The user wants comment language. Route to
instagram-audience-voiceafter a shortlist exists.
Collection Key Routing
Route to the matching hosted collection key by task shape:
- post or Reel samples from known accounts or URLs,
- hashtag-derived benchmark pools.
Discover the exact released collection keys and request shapes with
postplus research schema --json. Use hosted collection outputs and the
workflow below.
Default Workflow
- Define seeds: usernames, post URLs, Reel URLs, hashtags, or themes.
- Collect the first candidate pool at 10-15 posts or reels per theme.
- Normalize post and Reel-like results into one comparable dataset.
- Rank by engagement proxy, relevance, recency, and format fit.
- Produce a benchmark shortlist.
- Summarize repeated hooks, visual formats, caption patterns, and hashtag use.
Treat 10-15 posts or reels per theme as the first-pass boundary. Do not compile a wider first input from broad wording like "as many as possible." Expand only after the first shortlist proves seed quality and the user approves a second pass.
Good Output
Return top benchmark examples, content-type split, repeated opening patterns, value promises, likely content pillars, and recommended next posts to inspect deeper.
Failure Modes
- Stop if no usable benchmark seeds exist.
- Stop on unsupported keys, missing auth, unavailable hosted service, or stable network failure.
- Do not treat benchmark content as permission to contact creators directly;
lead work belongs in
creator-outreach.
Handoff
- Need creator pool from benchmark content ->
instagram-creator-discovery. - Need comment sentiment or audience language ->
instagram-audience-voice. - Need shot-level video breakdown ->
video-analysis.
Public Command Boundary
- Choose the smallest matching command or workflow from the user input and run it directly.
- Readiness diagnostics:
postplus doctor --skill instagram-content-benchmark. - If an owned CLI or script command fails, report the exact error and stop. Do not bypass the failure with metadata-only answers, readiness probing, local payload rewrites, fallback providers, or unpublished tools.
- Use
postplus research schema --collection-key <collectionKey> --jsononly when constructing or repairing an unknown request shape. - Hosted collection runs through the shared
research collectverb (owned by instagram-tools), attributing the run to this skill:postplus research collect <collectionKey> --skill instagram-content-benchmark --request <input.json> --output <result.json>(input = the collection parameters). - Resume a pending collection:
postplus research collect --run-handle <runHandle> --output <result.json>. - Keep the first pass bounded; expand only after inspecting the first result.
- If the CLI returns a quote-confirmation challenge, run
postplus quote confirm --json --challenge-file <challenge.json>and retry with the returned token.
FAQ
What does the instagram-content-benchmark skill do?
Benchmark Instagram posts and Reels to discover winning content patterns, shortlist high-value examples, and extract reusable hooks and formats.
How do I install instagram-content-benchmark?
Run npx skills add https://github.com/postplusai/postplus-skills --skill instagram-content-benchmark in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/instagram-content-benchmark/ (personal) or .claude/skills/instagram-content-benchmark/ (project).
Which AI agents can use instagram-content-benchmark?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is instagram-content-benchmark safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains instagram-content-benchmark?
It is published by postplusai in postplusai/postplus-skills. It has 525 recorded installs.
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