Browsing Bluesky Skill | Agent Skills

Browsing Bluesky

Access Bluesky content through public APIs and real-time firehose. Supports optional authentication for personalized feeds. Includes account analysis for categorization.

Implementation

Add skill directory to path and import:

import sys
sys.path.insert(0, '/path/to/skills/browsing-bluesky')  # or use .claude/skills symlink path
from browsing_bluesky import (
    # Core browsing
    search_posts, get_user_posts, get_profile, get_feed_posts, sample_firehose,
    get_thread, get_quotes, get_likes, get_reposts,
    get_followers, get_following, search_users,
    # Trending
    get_trending, get_trending_topics,
    # Account analysis
    get_all_following, get_all_followers, extract_post_text,
    extract_keywords, analyze_account, analyze_accounts,
    # Authentication utilities
    is_authenticated, get_authenticated_user, clear_session
)

Authentication (Optional)

Authentication enables personalized feeds (like Paper Skygest) that require knowing who's asking.

Setup

Create an app password at Bluesky: Settings → Privacy and Security → App Passwords

Set environment variables:

export BSKY_HANDLE="yourhandle.bsky.social"
export BSKY_APP_PASSWORD="xxxx-xxxx-xxxx-xxxx"

Behavior

Transparent: All functions work identically with or without credentials
Automatic: Auth headers are added opportunistically when credentials exist
Graceful: Failed auth silently falls back to public access
Secure: Tokens cached in memory only, never logged or persisted

Check Auth Status

if is_authenticated():
    print(f"Logged in as: {get_authenticated_user()}")
else:
    print("Using public access")

# Clear session if needed (e.g., switching accounts)
clear_session()

Research Workflows

Investigate a Topic

Use search_posts() with query syntax matching bsky.app advanced search:

Basic terms: event sourcing
Exact phrases: "event sourcing"
User filter: from:acairns.co.uk or use author= param
Date filter: since:2025-01-01 or use since= param
Hashtags, mentions, domain links: #python mentions:user domain:github.com

Combine query syntax with function params for complex searches.

Monitor a User

Fetch profile with get_profile(handle) for context (bio, follower count, post count)
Get recent posts with get_user_posts(handle, limit=N)
For topic-specific user content, use search_posts(query, author=handle)

Discover What's Trending

Recommended workflow — trending API first, firehose for deep dives:

1. Quick scan with trending topics (~500 tokens)

topics = get_trending_topics(limit=10)
# Returns: {topics: [{topic, display_name, description, link}, ...],
#           suggested: [...]}

2. Rich trends with post counts and actors

trends = get_trending(limit=10)
for t in trends:
    print(f"{t['display_name']} — {t['post_count']} posts ({t['status']})")
# Each trend includes: topic, display_name, link, started_at,
#   post_count, status, category, actors

3. Targeted exploration of selected trends

posts = search_posts(trend["topic"], limit=25)

4. Optional: Firehose for velocity monitoring or long-tail discovery

Prerequisites: Install Node.js dependencies once per session:

cd /home/claude && npm install ws https-proxy-agent 2>/dev/null

data = sample_firehose(duration=30)  # Full firehose sample
data = sample_firehose(duration=20, filter="python")  # Filtered sample

Returns dict with keys:

window: {startTime, endTime, durationSeconds} — sampling time range
stats: {totalReceived, totalPosts, postsPerSecond, filter, languages} — volume metrics and language breakdown
topWords: [[word, count], ...] — top 50 words (count >= 3)
topPhrases: [[bigram, count], ...] — top 30 bigrams (count >= 2)
topTrigrams: [[trigram, count], ...] — top 20 trigrams (count >= 2)
entities: [[entity, count], ...] — top 25 handles/hashtags (count >= 2)
samplePosts: [{text, altTexts, hasImages}, ...] — first 50 matching posts

Read Feeds and Lists

get_feed_posts() accepts:

List URLs: https://bsky.app/profile/austegard.com/lists/3lankcdrlip2f
Feed URLs: https://bsky.app/profile/did:plc:xxx/feed/feedname
AT-URIs: at://did:plc:xxx/app.bsky.graph.list/xyz

The function extracts the AT-URI from URLs automatically.

Explore a Thread

Fetch full thread context for a post with parents and replies:

thread = get_thread("https://bsky.app/profile/user/post/xyz", depth=10)
# Returns: {post: {...}, parent: {...}, replies: [...]}

Find Quote Posts

Discover posts that quote a specific post:

quotes = get_quotes("https://bsky.app/profile/user/post/xyz")
for q in quotes:
    print(f"@{q['author_handle']}: {q['text'][:80]}")

Analyze Engagement

Get users who engaged with a post:

likes = get_likes(post_url)
reposts = get_reposts(post_url)

# Accepts both URLs and AT-URIs
likes = get_likes("at://did:plc:.../app.bsky.feed.post/...")

Explore Social Graph

Navigate follower/following relationships:

followers = get_followers("handle.bsky.social")
following = get_following("handle.bsky.social")

# Returns list of actor dicts with handle, display_name, did, description, etc.

Find Users

Search for users by name, handle, or bio:

users = search_users("machine learning researcher")
for u in users:
    print(f"{u['display_name']} (@{u['handle']}): {u['description'][:100]}")

API Endpoint Notes

Public AppView: https://api.bsky.app/xrpc/ for unauthenticated reads
PDS: https://bsky.social/xrpc/ for authenticated requests
Trending: app.bsky.unspecced.getTrends (rich) and app.bsky.unspecced.getTrendingTopics (lightweight)
Firehose: wss://jetstream1.us-east.bsky.network/subscribe
Endpoint routing is automatic - authenticated requests go to PDS, public requests go to AppView
Rate limits exist but are generous for read operations

Return Format

All API functions return structured dicts with:

uri: AT protocol identifier
text: Post content
created_at: ISO timestamp
author_handle: User handle
author_name: Display name
likes, reposts, replies: Engagement counts
links: Full URLs extracted from post facets (post text truncates URLs with "...")
image_alts: Alt text from embedded images
url: Direct link to post on bsky.app

Profile function returns: handle, display_name, description, followers, following, posts, did

Account Analysis

Analyze accounts for categorization by topic. Fetches profile and posts, extracts keywords, and returns structured data for Claude to categorize.

Analyze a User's Network

# Analyze accounts you follow
results = analyze_accounts(following="yourhandle.bsky.social", limit=50)

# Analyze your followers
results = analyze_accounts(followers="yourhandle.bsky.social", limit=50)

# Analyze specific handles
results = analyze_accounts(handles=["user1.bsky.social", "user2.bsky.social"])

Single Account Analysis

analysis = analyze_account("user.bsky.social")
# Returns: {handle, display_name, description, keywords, post_count, followers, following}

Keyword Extraction Options

Stopwords parameter filters domain-specific noise:

"en": English (general purpose, default)
"ai": AI/ML domain (filters tech boilerplate)
"ls": Life Sciences (filters research methodology)

results = analyze_accounts(following="handle", stopwords="ai")

Requires: extracting-keywords skill with YAKE venv for keyword extraction.

Filtering Accounts

results = analyze_accounts(
    following="handle",
    exclude_patterns=["bot", "spam", "promo"]  # Skip accounts matching these
)

Paginated Following/Followers

For large account lists beyond the 100 limit of get_following/get_followers:

all_following = get_all_following("handle", limit=500)  # Handles pagination
all_followers = get_all_followers("handle", limit=500)

Account Analysis Output

Each analyzed account returns:

{
    "handle": "user.bsky.social",
    "display_name": "User Name",
    "description": "Bio text here",
    "keywords": ["keyword1", "keyword2", "keyword3"],
    "post_count": 20,
    "followers": 1234,
    "following": 567
}

Claude uses bio + keywords to categorize accounts by topic without hardcoded rules

Agent Skills: Browsing Bluesky

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