Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add techwolf-ai/ai-first-toolkit/plugin install content-studioWrote 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/techwolf-ai/ai-first-toolkit/brainstorm-linkedin)<a href="https://agentmods.dev/skills/techwolf-ai/ai-first-toolkit/brainstorm-linkedin"><img src="https://agentmods.dev/badge/skills/techwolf-ai/ai-first-toolkit/brainstorm-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 | $0.00053 | $0.00532 |
| Opus 5 | $0.00026 | $0.00266 |
| Sonnet 5 | $0.00011 | $0.00106 |
| Haiku 4.5 | $0.00005 | $0.00053 |
Grade A, and why
brainstorm-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 6d 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.
What it actually says
Brainstorm LinkedIn Posts from Source Material
Generate LinkedIn post ideas based on external context provided by the user.
Process
-
Read ALL published posts (MANDATORY - to avoid topic/angle overlap):
./scripts/print-published.sh linkedin-postThis prints all published posts with full content in one call. Note:
- Core insights already covered
- Data points already used
- Angles already explored
Do not suggest ideas that repeat existing coverage.
-
Read the style guide:
guidelines/linkedin.mdreferences/professional-profile.md
-
Process the provided context (user will provide one or more of):
- Files (PDFs, documents, research papers)
- URLs (articles, blog posts, announcements)
- Raw text or ideas
-
Identify 2-4 promising angles by considering:
- What's the unique insight for a professional audience?
- How does this connect to the author's expertise?
- What's the hook that works in the first 210 characters?
- Is there a personal angle or company connection?
-
Present ideas with for each:
- Proposed title
- Core insight (1 sentence)
- Hook approach (personal anecdote, company experience, surprising outcome, or news)
- Why it fits the author's voice
-
Ask user to choose:
- Which idea(s) to develop
- Whether to create as idea (01-ideas) or draft (02-drafts)
Evaluation Criteria
Strong LinkedIn post ideas have:
- A concrete hook in the first 210 characters
- A clear insight that provides value
- Connection to the author's expertise areas
- Room for a personal or company angle
- Appropriate scope for the target word count
Creating Files
After user selection, get timestamp:
date -u +"%Y%m%d-%H%M%S" # For slug
date -u +"%Y-%m-%dT%H:%M:%S.000Z" # For created/lastUpdated
Create file at: content/posts/linkedin-post/{slug}-{slugified-title}.yaml
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.
- 6d ago First seen · 66 lines · 53 tokens per session scan A 27d2ca8f63dd
brainstorm-linkedin is a skill published in the GitHub repository techwolf-ai/ai-first-toolkit (98 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 532 once invoked, about $0.0003 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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