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 skills/maxtechera/ship/distributionnpx skills add maxtechera/ship --skill distributiongit clone --depth 1 https://github.com/maxtechera/shipWhat 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 | $0.00018 | $0.00634 |
| Opus 5 | $0.00009 | $0.00317 |
| Sonnet 5 | $0.00004 | $0.00127 |
| Haiku 4.5 | $0.00002 | $0.00063 |
Grade A, and why
content-distribution 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 yesterday.
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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Distribution
Publish content to the right platforms at the right time.
Channel Tiers
Tier 1 — API/Automation Ready
- Instagram — reels, carousels, stories via Meta Graph API
- Newsletter — MailerLite campaigns and subscriber management
- Telegram — direct messaging to groups
Tier 2 — Semi-Manual (prepare assets, upload via platform UI)
- TikTok — prepare captions + hashtags, manual upload
- YouTube Shorts — prepare metadata, manual upload
- Twitter/X — compose + schedule via platform
- LinkedIn — compose + post via platform
Pre-Distribution Checklist
Before publishing any asset:
- Asset QA complete (copy humanized, visuals crop-safe)
- UTM links generated for all CTAs
- Platform formatting verified (aspect ratio, caption length, hashtags)
- Event tracking confirmed (GA4 events will fire on click)
- Schedule confirmed (time + timezone)
UTM Generation
Every link in published content must include UTM parameters:
utm_source = platform (instagram, newsletter, tiktok, linkedin)
utm_medium = format (reel, carousel, story, email, post)
utm_campaign = run name or content series slug
utm_content = specific asset identifier
Generate a UTM manifest (CSV) for each content batch:
asset_id, platform, format, url, utm_source, utm_medium, utm_campaign, utm_content, full_utm_url
Schedule Format
[
{
"date": "YYYY-MM-DD",
"time": "HH:MM",
"platform": "instagram",
"format": "reel",
"asset_id": "...",
"caption": "...",
"hashtags": [...],
"link_in_bio": true
}
]
Post-Publish Confirmation
After publishing, log:
- Published URL / permalink
- Timestamp
- Platform and format
- UTM link confirmed in post
This becomes the measurement baseline for content-measure.
Rules
- Never auto-publish to personal social accounts — prepare + confirm with owner
- Draft autoscheduling is allowed; live publishing requires explicit approval
- Hashtag research per platform (Instagram: 5-10 relevant, TikTok: 3-5)
- Cross-posting: adapt format per platform, never copy-paste across
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.
- yesterday First seen · 92 lines · 18 tokens per session scan A 927e62b3de44
content-distribution is a skill published in the GitHub repository maxtechera/ship (2 stars, last pushed 4mo ago), licensed MIT. It adds 18 tokens to every session and 634 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 skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…