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.
npx agentmods add commands/brainbytes-dev/everything-claude-marketing/social-postgit clone --depth 1 https://github.com/brainbytes-dev/everything-claude-marketingWhat 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 | $0.00028 | $0.01106 |
| Opus 5 | $0.00014 | $0.00553 |
| Sonnet 5 | $0.00006 | $0.00221 |
| Haiku 4.5 | $0.00003 | $0.00111 |
Grade A, and why
social-post 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/social-post
Create platform-native social media content that fits the conventions, algorithms, and audience expectations of each platform. Supports X, LinkedIn, Instagram, TikTok, YouTube, and more.
What This Command Does
The /social-post command generates ready-to-publish social media content adapted to each specified platform. It handles the nuances that matter — character limits, hashtag strategies, hook formats, content structure, and engagement patterns unique to each network. When you specify multiple platforms, each post is independently crafted rather than copy-pasted across channels.
The command delegates to the social-media-manager agent, which understands platform-specific best practices, algorithm preferences, and audience behavior patterns.
When to Use
- You are announcing company news, product launches, or milestones
- You need to promote blog posts, case studies, or other content
- You want to share thought leadership or industry insights
- You are building a content calendar and need draft posts
- You need to repurpose one piece of content across multiple platforms
- You want to create engagement-focused posts (polls, questions, threads)
- You are drafting posts for executives or team members
How It Works
- Platform Selection — Identifies which platforms to create content for
- Message Extraction — Distills the core message, news, or story from your input
- Format Optimization — Selects the best content format for each platform (thread, carousel outline, short-form video script, single post, etc.)
- Hook Engineering — Crafts attention-grabbing opening lines tuned to each platform's scroll behavior
- Content Structuring — Formats the body content using platform-native patterns (line breaks, emojis, bullet points as appropriate)
- CTA & Engagement — Adds platform-appropriate calls to action and engagement prompts
- Hashtag & Keyword Strategy — Includes relevant hashtags or keywords based on platform norms
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 · 139 lines · 28 tokens per session scan A 717ccf5ce0df
social-post is a command published in the GitHub repository brainbytes-dev/everything-claude-marketing (5 stars, last pushed 5mo ago), licensed MIT. It adds 28 tokens to every session and 1,106 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
git
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checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.