threads-keyword-search
Searches Threads posts by keyword or hashtag and returns matching posts with engagement metrics, extracted from SSR-embedded JSON.
Skill by browser-act
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/browser-act-threads-keyword-search
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: writing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 2
codeload.github.com· found in install commandthreads.com· found in code
Files it touches
~/.claude/skills/threads-keyword-search
What's inside
- Skill name
threads-keyword-search- Description
- Searches Threads posts by keyword or hashtag and returns matching posts with engagement metrics, extracted from SSR-embedded JSON. Use when user asks to search Threads posts, find Threads content by topic, scrape Threads search results, collect Threads posts about a keyword, monitor Threads hashtag activity, pull Threads posts mentioning a term, gather Threads content by hashtag, search for posts on Threads, extract Threads search feed, get trending posts on Threads, find Threads discussions about a subject, or fetch recent or top Threads posts by keyword.
- License
- MIT
- Instructions
- 127 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (2)
- SKILL.md
- extract-search-results.py · scripts/
SKILL.md (first lines)
# Threads — Keyword & Hashtag Search
> keyword + sort filter → list of matching posts with engagement metrics
## Language
All process output to user (progress updates, process notifications) follows the user's language.
## Objective
Search Threads for posts matching a keyword or hashtag and extract the results from SSR-embedded JSON, with support for top/recent sort ordering.
## Prerequisites
- A browser is open and connected via browser-act
- No login required for public search results (unauthenticated: typically 17-18 results per query, no pagination)
## Pre-execution Checks
### 1. Tool Readiness
If browser-act has been confirmed available in the current session → skip this step.
Invoke `browser-act` via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.
## Capability Components
> This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page. JS code is encapsulated in Python files under the `scripts/` directory, invoked via `eval "$(python scripts/xxx.py {params})"`. `$(...)` is bash syntax; it is recommended to use the bash tool for execution.
### SSR: Extract keyword search results
Navigate to the search page with the keyword and sort filter, then extract all results embedded in the initial HTML:
1. `navigate https://www.threads.com/search/?q={keyword}&serp_type={filter}`
- `{keyword}`: URL-encoded search term or hashtag (e.g., `AI` or `%23AI` for `#AI`)
- `{filter}`: `top` (default, most relevant) or `recent` (chronologically newest)
2. `wait stable`
3. `eval "$(python scripts/extract-search-results.py '{keyword}' --filter {filter})"`
Output example:
```json
{
"keyword": "AI",
"filter": "top",
"posts": [
{
"id": "3936653356768062022", // post internal ID (pk)
"code": "DZyvcdEl-W1", // post short code for URL
"url": "https://www.threads.com/@flower_popy/post/DZyvcdEl-W1",
"text": "AI is changing everything...", // post text content, null if no caption
"taken_at": 1781926571, // Unix timestamp of post creation
"like_count": 34, // number of likes
"reply_count": 6, // number of direct replies
"repost_count": 0, // number of reposts
"quote_count": 0, // number of quote posts
"is_reply": false, // true if this post is a reply
"media_type": 19, // 1=photo, 2=video, 8=carousel, 19=text-only
"has_media": false, // true if post contains image/video/carousel
"user": {
"pk": "14803522782",
"username": "flower_popy",
"full_name": "Flower",
"is_verified": false
}
}
],
"count": 17,
"page_info": {
"end_cursor": null,
"has_next_page": false,
"has_previous_page": false,
"start_cursor": null
}
}
```
Error handling: If `error: true` is returned, check that the search page loaded correctly by verifying the URL contains the query parameter. If `searchResults not found`, the page may have failed to render SSR data — retry `navigate` and `wait stable` once. If `count: 0`, no posts matched the keyword.
### SSR: Hashtag search
Hashtag search uses the same URL pattern. Prefix keyword with `#`:
1. `navigate https://www.threads.com/search/?q=%23{hashtag}&serp_type={filter}`
- Example: `%23AI` for `#AI`
2. `wait stable`
3. `eval "$(python scripts/extract-search-results.py '#AI' --filter top)"`
The `#` prefix in the keyword argument is for labeling only; the URL encoding `%23` is what Threads uses to identify hashtag searches.
## Enum Parameters
[DOM] filter — values: `top` (most relevant/popular posts), `recent` (newest posts first). Set via `--filter` argument and `serp_type` URL parameter.
## Pagination
Pagination is not available for unauthenticated access on the search endpoint (`has_next_page: false` is returned regardless of result volume). Results are limited to approximately 17-18 posts per query without login. For broader coverage, run multiple searches with related keywords.
## Success Criteria
`result.count >= 1` and `result.posts[0].id != null` and `result.posts[0].user.username != null`
## Known Limitations
- Unauthenticated access: no pagination; approximately 17-18 results per keyword
- Date filtering is not supported as a URL parameter; filter by `taken_at` (Unix timestamp) client-side after extraction
- Private account posts may appear in search results but their full content may be restricted
- Search index may not include very new posts (lag of minutes to hours)
## Execution Efficiency
- **Batch orchestration**: Write a bash script to loop keywords serially within a single session. Add 1-2 second intervals between searches. For higher throughput, distribute keywords across multiple parallel browser sessions.
- **Test before batch execution**: Test with 1-2 keywords first before running full batch.
- **Reduce redundant pre-operations**: Each keyword requires a fresh `navigate` to the search URL — the search parameters are baked into the URL.
- **Error resumption**: Save results per keyword; on failure, resume from the breakpoint.
## Experience Notes
Path: `{working-directory}/browser-act-skill-forge-memories/threads-scraper-threads-keyword-search.memory.md`From browser-act/skills, MIT.
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Signals
- Stars
- 6,268
- Forks
- 330
- Open issues
- 9
- Last commit (this folder)
- Jul 20, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/browser-act/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
threads-keyword-search skill. Agent Mart. https://agentmart.dev/skills/browser-act-threads-keyword-search (last updated 2026-10-24)