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/classicchins/compounding-marketingWrote 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/classicchins/compounding-marketing/cm-social)<a href="https://agentmods.dev/commands/classicchins/compounding-marketing/cm-social"><img src="https://agentmods.dev/badge/commands/classicchins/compounding-marketing/cm-social/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/commands/classicchins/compounding-marketing/cm-social"><img src="https://agentmods.dev/badge/commands/classicchins/compounding-marketing/cm-social.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 | $0.00000 | $0.02939 |
| Opus 5.5 | $0.00000 | $0.01176 |
| Sonnet 5.5 | $0.00000 | $0.00588 |
| Haiku 4.5 | $0.00000 | $0.00294 |
Grade A, and why
cm-social 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.
How it starts
The opening of the file, as written. The whole thing — 459 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/cm:social — Social Media Campaign Planning
Plan and execute a complete social media campaign across platforms with clear goals, content calendar, and engagement tactics.
What It Does
Guides you through social campaign planning from goal-setting to execution, with platform-specific strategies and a 30-day content calendar template.
Process
Step 1: Define Campaign Goal
Choose ONE primary goal:
Awareness → Reach new audiences, build brand visibility
- Metrics: Impressions, reach, follower growth
- Platforms: Twitter (virality), LinkedIn (B2B reach), Instagram (visual)
Engagement → Build community, start conversations
- Metrics: Likes, comments, shares, reply rate
- Platforms: Twitter (conversations), LinkedIn (thought leadership), Reddit (niche communities)
Conversion → Drive signups, demos, downloads
- Metrics: Link clicks, conversions, cost per acquisition
- Platforms: LinkedIn (B2B), Facebook/Instagram (paid ads), Twitter (DMs)
Write your goal:
"Increase [metric] by [X%] in [timeframe] via [platforms]"
Example:
"Increase demo bookings by 30% in 30 days via LinkedIn + Twitter organic content"
Step 2: Platform Selection
Match platform to goal + audience:
LinkedIn (B2B Decision-Makers)
Best for:
- Thought leadership
- B2B SaaS positioning
- Recruitment / employer branding
- CEO / executive visibility
Content that works:
- Personal stories (career lessons, founder journey)
- Industry insights (hot takes, trend analysis)
- How-to guides (tactical value)
- Company milestones (funding, launches, hiring)
Frequency: 3-5 posts/week (consistency > volume)
Engagement tactics:
- Comment on other posts (first-comment strategy)
- Tag relevant people (not spammy)
- Use carousels (higher engagement than single images)
- Native video > external links (LinkedIn prioritizes native)
Twitter/X (Developers, Tech Enthusiasts, Early Adopters)
Best for:
- Real-time updates
- Product launches (tech audience)
- Viral reach (retweets > likes)
- Customer support / community
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 · 459 lines · 0 tokens per session scan A 2078ecb3e3e3
cm-social is a command published in the GitHub repository classicchins/compounding-marketing (8 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,939 tokens. 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.
cm-social compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| cm-socialclassicchins/compounding-marketing | Command | 8 | 5mo ago | MIT | A | 0 | Claude Code |
| checklistgithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| clarifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 27 | Claude Code |
| specifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| analyzegithub/spec-kit | Command | 148k | yesterday | MIT | A | 26 | Claude Code |
| convergegithub/spec-kit | Command | 148k | yesterday | MIT | A | 35 | Claude Code |
| implementgithub/spec-kit | Command | 148k | yesterday | MIT | A | 14 | Claude Code |