Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/oaustegard/claude-skills/categorizing-bsky-accounts)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/categorizing-bsky-accounts"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/categorizing-bsky-accounts/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/oaustegard/claude-skills/categorizing-bsky-accounts"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/categorizing-bsky-accounts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.01724 |
| Opus 5 | $0.00022 | $0.00862 |
| Sonnet 5 | $0.00009 | $0.00345 |
| Haiku 4.5 | $0.00004 | $0.00172 |
Grade A, and why
categorizing-bsky-accounts scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Categorizing Bluesky Accounts
Fetch Bluesky account data and extract keywords for Claude to categorize by topic. The script compresses account context (bio + posts) into bio + keywords, then Claude performs intelligent categorization.
Prerequisites
Requires: extracting-keywords skill (provides YAKE venv + domain stopwords)
The analyzer delegates keyword extraction to the extracting-keywords skill, which provides:
- Optimized YAKE installation with minimal dependencies
- Domain-specific stopwords: English (574), AI/ML (1357), Life Sciences (1293)
- Support for 34 languages
Core Workflow
When users request Bluesky account analysis:
-
Ensure keyword extraction is set up - Invoke the extracting-keywords skill using the Skill tool to ensure YAKE venv exists (skip if already invoked in this session)
-
Determine input mode based on user's request:
- Following list → use
--following handle - Followers → use
--followers handle - List of handles → use
--handles "h1,h2,h3" - File provided → use
--file accounts.txt
- Following list → use
-
Configure parameters:
--accounts N- Number to analyze (default: 100, max: 100)--posts N- Posts per account (default: 20, max: 100)--stopwords [en|ai|ls]- Choose domain-specific stopwords:en: English (general purpose)ai: AI/ML domain (recommended for tech accounts)ls: Life Sciences (for biomedical/research accounts)
--exclude "pattern1,pattern2"- Skip spam/bot accounts
-
Run script - Outputs simple text format to stdout:
@handle1.bsky.social (Display Name) Bio text here Keywords: keyword1, keyword2, keyword3 @handle2.bsky.social (Another Name) Bio text here Keywords: keyword4, keyword5, keyword6 -
Categorize accounts - Claude analyzes bio + keywords to categorize by topic
Quick Start
Analyze following list with AI/ML stopwords:
python scripts/bluesky_analyzer.py --following austegard.com --stopwords ai
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago Changed · -36 lines e5963f103df7
- 12d ago First seen · 274 lines · 44 tokens per session scan A 1e4cae7e9bb6
categorizing-bsky-accounts is a skill published in the GitHub repository oaustegard/claude-skills (148 stars, last pushed 2d ago), licensed MIT. It adds 44 tokens to every session and 1,724 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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