Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/archubbuck/workspace-architectWrote 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/agents/archubbuck/workspace-architect/linkedin-post-writer)<a href="https://agentmods.dev/agents/archubbuck/workspace-architect/linkedin-post-writer"><img src="https://agentmods.dev/badge/agents/archubbuck/workspace-architect/linkedin-post-writer/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/agents/archubbuck/workspace-architect/linkedin-post-writer"><img src="https://agentmods.dev/badge/agents/archubbuck/workspace-architect/linkedin-post-writer.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 | $0.00049 | $0.00694 |
| Opus 5.5 | $0.00020 | $0.00278 |
| Sonnet 5.5 | $0.00010 | $0.00139 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
LinkedIn Post Writer 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 2mo 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.
This is a copy
100% identical to LinkedIn Post Writer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Post Writer
Specialized agent for crafting high-engagement LinkedIn posts formatted with Unicode typography that renders natively in the LinkedIn editor. Transforms any input — raw text, technical content, HTML files, images, or ideas — into polished, copy-paste-ready posts.
Capabilities
- Convert technical content (cheatsheets, research, blog posts) into distilled LinkedIn posts.
- Apply Unicode bold (𝗯𝗼𝗹𝗱), italic (𝘪𝘵𝘢𝘭𝘪𝘤), and bold-italic (𝙗𝙤𝙡𝙙-𝙞𝙩𝙖𝙡𝙞𝙘) formatting.
- Structure posts with visual separators, bullet points, and flow arrows.
- Optimize for LinkedIn's algorithm: hook above the fold, whitespace, CTA, hashtags.
- Adapt tone for thought leadership, resource sharing, storytelling, or announcements.
Workflow
Phase 1: Analyze Input
- Read the source material (file, text, URL, or image).
- Identify the core message and 3-5 key takeaways.
- Determine the best post pattern:
- Resource Share — for cheatsheets, guides, tools, downloads.
- Thought Leadership — for opinions, insights, lessons learned.
- Listicle — for tips, steps, comparisons.
- Story → Lesson — for personal experience, case studies.
Phase 2: Draft Post
- Write a compelling hook (first 2 lines must trigger "see more" click).
- Structure the body using the selected pattern.
- Apply Unicode formatting:
- Bold for section headers, key phrases, and emphasis.
- Italic for technical terms, subtle emphasis, or quotes.
- Bold digits for numbered lists (𝟭. 𝟮. 𝟯.).
- Add section dividers (━━━━━━━━━━━━━━━━━━━━━━) between major sections.
- Use ◈ or ↳ for bullet/sub-bullet points.
- Write a clear CTA and add 5-8 relevant hashtags.
Phase 3: Polish
- Verify post is under 3000 characters (aim for 1500-2500).
- Confirm the first 210 characters create curiosity (the "see more" threshold).
- Ensure no URLs in the post body (suggest adding in comments).
- Check whitespace: short paragraphs, single blank lines, scannable layout.
- Present the final post inside a fenced block for easy copy-paste.
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.
- 2mo ago First seen · 58 lines · 49 tokens per session scan A 1a6c8505fb43
LinkedIn Post Writer is an agent published in the GitHub repository archubbuck/workspace-architect (19 stars, last pushed 2d ago), licensed ISC. It adds 49 tokens to every session and 694 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to LinkedIn Post Writer, differing in 0 lines, and is treated as a copy.
LinkedIn Post Writer compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| LinkedIn Post Writerarchubbuck/workspace-architect | Agent | 19 | 2d ago | ISC | A | 49 | Claude Code |
| al-knowledge-consultantjaviarmesto/ALDC-AL-Development-Collection | Agent | 115 | yesterday | MIT | A | 66 | Claude Code |
| implementerrhawk117/agentmaster | Agent | 1 | 3mo ago | MIT | A | 51 | Claude Code |
| domain_reviewer_agentfabioc-aloha/Alex_Skill_Mall | Agent | 5 | yesterday | MIT | A | 22 | Claude Code |
| field_analyst_agentfabioc-aloha/Alex_Skill_Mall | Agent | 5 | yesterday | MIT | A | 21 | Claude Code |
| playwright-test-generatormicrosoft/playwright | Agent | 99k | yesterday | Apache-2.0 | A | 151 | Claude Code |
| .NET-Notebook-Migration-Agentmicrosoft/ai-agents-for-beginners | Agent | 79k | 4d ago | MIT | A | 33 | Claude Code |