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Threads Data Skill

The Threads Data Skill is the source-sliced data guide a Platform Agent owns: it names the concrete `threads/...` operations, response shapes, and gotchas for reading Meta's public Threads surface through UnifAPI MCP, so any text-first listening or content research runs from one deterministic workflow. Read-only — it never posts.

Agent-native

Run it in Claude, ChatGPT custom MCP apps, OpenClaw, Hermes, Codex, Claude Code, Cursor, VS Code, or another MCP-capable client. No dedicated GUI flow and no separate LLM API key.

Backed by live public data

Every step is grounded in live public-data records UnifAPI returns, so the output cites what is actually ranking, posting, or being said — not a generic best-practice list.

Composable & open source

Skills cross-reference each other and live in a public, MIT-style repo. Read the full SKILL.md on GitHub, fork it, or run it as-is inside your agent.

Run prompt

Paste this into Codex or Claude Code

The prompt is intentionally editable. Replace the handles, market, budget, and campaign goal, then let the agent call UnifAPI MCP when it needs live public data.

Using the Threads Data Skill, research our brand term: pull the recent and top post search for the term, plus relevant profiles and their replies. Return a cited listening brief. Read-only.
How the skill works

The full skill, rendered from its SKILL.md

The deterministic read path for public Threads (Meta) data through UnifAPI. This is a Data Skill: it does not run a marketing job on its own — it names the concrete threads/... operations, response shapes, and gotchas so any text-first listening or content workflow reads from one known recipe instead of rediscovering the surface each time.

Read-only — eyes, not hands. It researches public Threads data and returns cited records; it never posts or replies, and UnifAPI never holds Threads credentials.

Use the unifapi skill for live evidence

Connect once through the shared unifapi skill (OAuth MCP), then call the operations below. Profiles are keyed by {username}. Keep any billing metadata so the output can state record cost.

Response contract

Single-entity endpoints return the object in data:

{
  "request_id": "unif_...",
  "data": {},
  "billing": { "records_charged": 1, "balance_remaining": 99 }
}

List endpoints return an array in data plus pagination:

{
  "request_id": "unif_...",
  "data": [],
  "pagination": { "has_more": false, "next_cursor": null },
  "billing": { "records_charged": 1 }
}

When pagination.has_more is true, pass pagination.next_cursor as the next request's cursor. Always preserve billing when reporting cost.

Core operations

NeedOperation
Newest posts on a termthreads/search/recent (?q=...)
Most-seen posts on a termthreads/search/top (?q=...)
Profiles on a termthreads/search/profiles (?q=...)
Profile by handlethreads/users/{username}
A handle's poststhreads/users/{username}/posts
A handle's repliesthreads/users/{username}/replies
A handle's repoststhreads/users/{username}/reposts

Need a field not listed here? Use the unifapi skill's get_operation to read the exact schema before calling — but pick the operation from this table, don't discover blind.

Workflow

The deterministic recipes. Pick the one that matches the job; each names exactly what to call.

  1. Set the term. For brand or category listening, call threads/search/recent?q=... (newest) and threads/search/top?q=... (most-seen) together — recent catches the live conversation, top catches the takes that actually spread. Page via next_cursor.
  2. Find handles. Call threads/search/profiles?q=... to surface accounts on the term, then threads/users/{username} for follower size and biography.
  3. Read a profile's activity. Call threads/users/{username}/posts, .../replies, and .../reposts for what a handle says, answers, and amplifies.
  4. Cluster takes. Group text across the recent and top results into questions and opinions; like_count ranks which takes resonate.
  5. Cite everything. Every quote ties back to its post or profile; report billing.records_charged (or estimate when billing metadata is absent).

Shape notes

  • ThreadsUser — keyed by {username}. full_name, biography, follower_count, is_verified, is_private.
  • ThreadsPostcode (the URL segment), text, taken_at, like_count, image_url, video_url, user.

Gotchas

  • search/recent is the newest and search/top is the most-seen — use both for a balanced read; either alone skews recency or popularity.
  • Posts expose like_count only — there are no reply/repost counts on the post object. Gauge spread from the search/top ranking, not a repost number.
  • A private handle (is_private) limits what you can read — surface it.
  • A low balance can silently truncate list pages: check billing.truncated_due_to_balance — when true the page is partial.

Output

Return the records the calling workflow needs, each cited to its post or profile, plus a one-line cost note (records_charged). When this skill is used directly, a compact listening brief is the default:

**"{term}" on Threads** — {N} recent / {N} top posts. Takes: {themes}. Loudest: "{quote}" ({likes} likes, by @handle). Evidence: {post URLs}. Records: ~{N}.
  • social-listening-brief (Social Listening), content-opportunity-brief (Content Strategy) — listening and content-idea work on top of this read path.
  • unifapi — the shared data skill: connect MCP and look up exact schemas with get_operation.

Source: threads/SKILL.md on GitHub — open a PR there to improve it.

Public-data tools

The live APIs this skill calls

Every operation the skill names is one of these UnifAPI platforms — still visible and callable for product code, debugging, and custom agent flows.

  • The concrete `threads/...` operations for each common listening read job
  • Response-contract and shape notes for posts and profiles
  • Deterministic recipes: recent vs. top search, profile, replies
  • Platform gotchas (recent vs. top, like_count only, cursor pagination)