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/Rainbowlight-pixel/claude-cowork-content-pluginWrote 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/commands/rainbowlight-pixel/claude-cowork-content-plugin/linkedin)<a href="https://agentmods.dev/commands/rainbowlight-pixel/claude-cowork-content-plugin/linkedin"><img src="https://agentmods.dev/badge/commands/rainbowlight-pixel/claude-cowork-content-plugin/linkedin.svg" alt="Measured on agentmods" 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 | $0.00007 | $0.00111 |
| Opus 5 | $0.00003 | $0.00056 |
| Sonnet 5 | $0.00001 | $0.00022 |
| Haiku 4.5 | $0.00001 | $0.00011 |
Grade A, and why
linkedin 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 7d 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 — 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.
What it actually says
Generate LinkedIn posts from the following content: $ARGUMENTS
Use the linkedin-post skill to create the posts. Follow these steps:
- Read the source content thoroughly
- Ask the user how many LinkedIn posts they want
- Generate the requested number of posts following LinkedIn best practices
- Each post should have a unique angle and style
- Save all posts to a markdown file in the workspace folder
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.
- 7d ago First seen · 15 lines · 7 tokens per session scan A 4f5433ee1c46
linkedin is a command published in the GitHub repository Rainbowlight-pixel/claude-cowork-content-plugin (6 stars, last pushed yesterday), licensed MIT. It adds 7 tokens to every session and 111 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to linkedin, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
memory-list
DEPRECATED: Use Serena listmemories instead. Lists recent memories from Forgetful with optional project filtering.
memory-search
Search memories semantically using Forgetful with query context for improved ranking. Use when retrieving specific knowledge or verifying memory existence.
validate-pr-description
Use when validating a PR title and description for conventional commit format, issue linking keywords, and template compliance before submission.
analyst
Use when performing local analyst review before pushing PR changes. Assesses code quality, impact analysis, and maintainability.
spec
Define what to build. Transform a problem into testable requirements with acceptance criteria.
plan
Plan how to build it. Decompose specs into milestones with dependencies and risk mitigations. Run after /spec.