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.
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.
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
| Need | Operation |
|---|---|
| Newest posts on a term | threads/search/recent (?q=...) |
| Most-seen posts on a term | threads/search/top (?q=...) |
| Profiles on a term | threads/search/profiles (?q=...) |
| Profile by handle | threads/users/{username} |
| A handle's posts | threads/users/{username}/posts |
| A handle's replies | threads/users/{username}/replies |
| A handle's reposts | threads/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.
- Set the term. For brand or category listening, call
threads/search/recent?q=...(newest) andthreads/search/top?q=...(most-seen) together — recent catches the live conversation, top catches the takes that actually spread. Page vianext_cursor. - Find handles. Call
threads/search/profiles?q=...to surface accounts on the term, thenthreads/users/{username}for follower size andbiography. - Read a profile's activity. Call
threads/users/{username}/posts,.../replies, and.../repostsfor what a handle says, answers, and amplifies. - Cluster takes. Group
textacross the recent and top results into questions and opinions;like_countranks which takes resonate. - 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.ThreadsPost—code(the URL segment),text,taken_at,like_count,image_url,video_url,user.
Gotchas
search/recentis the newest andsearch/topis the most-seen — use both for a balanced read; either alone skews recency or popularity.- Posts expose
like_countonly — there are no reply/repost counts on the post object. Gauge spread from thesearch/topranking, 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}.
Related skills
- 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.
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)