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instagram-audience-voice

instagram-audience-voice

github.com/postplusaiMarketing & growth27505 installsUpdated 1d ago
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About instagram-audience-voice

instagram-audience-voice is a skill for analyzing comments on a small, selected set of Instagram posts or Reels. It groups audience language by theme and intent to surface questions, objections, purchase signals, and reusable copy.

Key features

  1. 01Collect comments from selected posts
  2. 02Group comments by theme and intent
  3. 03Separate strong signals from low-signal reactions
  4. 04Identify questions and objections
  5. 05Extract reusable audience phrases

Use cases

  1. 01Analyze comments on competitor posts
  2. 02Find recurring questions about a product
  3. 03Identify purchase or trial intent signals
  4. 04Collect audience wording for campaign copy

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/postplusai/postplus-skills --skill instagram-audience-voice

After installing, type/instagram-audience-voicein Claude Code to confirm it loaded.

Details

From the project README

Instagram Audience Voice

Use this skill to mine Instagram comments for audience language, pain points, objections, FAQs, purchase intent, and reusable copy phrases.

Apply shared rulebook and user-guidance rules from postplus-shared.

Entry Requirement

Do not start from a huge blind post set. Prefer one of these first:

  • a benchmark shortlist from instagram-content-benchmark,
  • manually provided post or Reel URLs,
  • a small set of competitor top posts.

Collection Key Routing

Route to the matching hosted collection key by task shape: comments for a bounded set of shortlisted posts or Reels.

Discover the exact released collection keys and request shapes with postplus research schema --json. Use hosted collection outputs and the workflow below.

Default Workflow

  1. Confirm the post or Reel shortlist.
  2. Collect comments with instagram-comments.
  3. Normalize comments.
  4. Cluster comments by theme and intent.
  5. Separate high-signal language from low-signal reactions.
  6. Summarize actionable audience voice.

Keep raw comments and clustering caches under .postplus/; return reusable copy notes or summaries where the user can inspect them.

Suggested Buckets

  • praise
  • objection
  • question
  • purchase-intent
  • request-for-details
  • low-signal / meme

Good Output

Return top comment themes, repeated questions, objections, skepticism, purchase or trial intent signals, exact phrases worth reusing in copy, and comments that suggest unmet needs.

Failure Modes

  • Stop if no shortlist or post URLs are available.
  • Stop on unsupported keys, missing auth, unavailable hosted service, or stable network failure.
  • Do not infer full audience truth from comments without naming that comments are a public proxy.

Handoff

Turn audience language into hooks, offers, captions, or creative briefs through the relevant campaign, copy, or creative workflow.

Public Command Boundary

  • Choose the smallest matching command or workflow from the user input and run it directly.
  • Readiness diagnostics: postplus doctor --skill instagram-audience-voice.
  • 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> --json only when constructing or repairing an unknown request shape.
  • Hosted collection runs through the shared research collect verb (owned by instagram-tools), attributing the run to this skill: postplus research collect <collectionKey> --skill instagram-audience-voice --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.

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