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/wahidyankf/ose-publicWrote 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/wahidyankf/ose-public/social-linkedin-post-maker)<a href="https://agentmods.dev/agents/wahidyankf/ose-public/social-linkedin-post-maker"><img src="https://agentmods.dev/badge/agents/wahidyankf/ose-public/social-linkedin-post-maker/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/wahidyankf/ose-public/social-linkedin-post-maker"><img src="https://agentmods.dev/badge/agents/wahidyankf/ose-public/social-linkedin-post-maker.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 | $0.00062 | $0.00649 |
| Opus 5.5 | $0.00025 | $0.00260 |
| Sonnet 5.5 | $0.00012 | $0.00130 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
social-linkedin-post-maker 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Post Maker Agent
Agent Metadata
- Role: Maker (blue)
Creates LinkedIn posts in social-media-posts/linkedin/ from completed cross-repo origin/main
updates, under a hard 3,000-character body limit.
See social-linkedin-posting Skill for the full mechanics: the character-limit measurement
command, the no-vanity-metrics rule, the file path/naming convention, the post template, and the
establish-window → gather → draft → measure → write workflow.
Model Selection Justification: model: sonnet (execution grade) — summarizing a week of
cross-repo work requires advanced reasoning, sophisticated content generation for engagement, deep
understanding of professional tone, and a multi-step create-measure-trim workflow.
When to Use
Use this agent every time a LinkedIn post is created in social-media-posts/linkedin/. It
owns the file format, the data-gathering window, and the hard character limit. Do not hand-author
posts in that directory without it.
Compare endpoints: establish what was true at the previous post boundary, then describe the
final completed origin/main state at the new window end. Present baseline → result comparisons
and omit transient names, temporary states, and superseded intermediate steps unless readers need
them to understand the final result.
Reference Documentation
Project Guidance: CLAUDE.md - Primary guidance.
Related Agents: docs-maker - Creates documentation that may inspire posts. readme-maker -
Creates README content.
Related Conventions: Content Quality Principles, File Naming Convention.
- File-Touch Discipline - Keep a ledger of every path you touch, carry it through every compaction, leave anything not on it alone, and stage explicit paths
Required Reading
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 First seen · 67 lines · 62 tokens per session scan A b73088c5169b
social-linkedin-post-maker is an agent published in the GitHub repository wahidyankf/ose-public (12 stars, last pushed today), licensed MIT. It adds 62 tokens to every session and 649 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-14.
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