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 skills add oyi77/1ai-skills --skill planner-autogit clone --depth 1 https://github.com/oyi77/1ai-skillsWrote 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/oyi77/1ai-skills/planner-auto)<a href="https://agentmods.dev/skills/oyi77/1ai-skills/planner-auto"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/planner-auto/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/skills/oyi77/1ai-skills/planner-auto"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/planner-auto.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.02055 |
| Opus 5 | $0.00019 | $0.01027 |
| Sonnet 5 | $0.00008 | $0.00411 |
| Haiku 4.5 | $0.00004 | $0.00205 |
Grade A, and why
content-planner-auto 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.
How it starts
The opening of the file, as written. The whole thing — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Planner Auto
Auto-generate 30-day content calendars for your brand or clients. Revenue survival tool.
When to Use
Trigger phrases:
- "content planner auto"
- "Help me with content planner auto"
- "generate content calendar"
- "plan my content for the month"
Use cases:
- When the task matches this skill's domain expertise
- Creating monthly content calendars for clients
- Scheduling multi-platform content in batches
- Aligning content with seasonal events (especially Indonesian)
- Managing multiple brand/account content streams
When NOT to use:
- For tasks outside this skill's scope
- When real-time data is required (use live data feeds)
- For content requiring deep domain expertise you lack
- For legal, medical, or financial advice content
Overview
Content Planner Auto produces professional 30-day content calendars with pillar topic rotation, platform-optimized posting times, multi-account rotation, seasonal Indonesian event alignment, and PostBridge batch scheduling integration.
Money-Making Overview
Buyer Persona: SMEs, agencies, and e-commerce brands in Indonesia/US that post content but have no content strategy. They post when they remember. They need a calendar that keeps them consistent.
Pricing Tiers:
| Tier | Price | What They Get |
|---|---|---|
| Monthly Calendar | $200/mo | 30-day calendar, 1 platform, pillar rotation + seasonal hooks |
| Multi-Platform | $500/mo | 30-day calendar across 3 platforms, timing optimized per platform, PostBridge scheduling |
| Retainer + Execution | $800/mo | Full calendar + caption writing + asset briefs + weekly performance note |
First-Dollar Timeline: Day 1 — run the script below for any client niche and deliver a calendar by end of day. $200 in your pocket.
First Action in 60 Minutes
Copy-paste this script. Replace NICHE, PLATFORMS, and BRAND_VOICE with a real client's info. It outputs a 30-day calendar CSV ready to send.
#!/usr/bin/env python3
# generate_calendar.py — 30-day content calendar for any niche
# Usage: python3 generate_calendar.py > calendar_<client>_<month>.csv
import csv, sys, json
from datetime import datetime, timedelta
from textwrap import dedent
# ── CLIENT CONFIG (edit these) ──────────────────────────────
CLIENT = "UrbanWear Indonesia"
NICHE = "streetwear fashion"
PLATFORMS = ["Instagram", "TikTok", "Shopee Feed"]
BRAND_VOICE = "edgy, Gen Z, casual Indonesian with English slang"
PILLARS = ["outfit inspo", "new arrivals", "styling tips", "behind the scenes", "customer looks"]
SEASONAL_HOOKS = [
"Hari Kemerdekaan special drop",
"Back to campus fit check",
"Rainy season layering guide",
]
# ────────────────────────────────────────────────────────────
HEADERS = ["Day", "Date", "Platform", "Pillar", "Topic", "Hook/Format", "CTA", "Assets Needed", "Notes"]
today = datetime.now().date()
rows = []
for day_offset in range(30):
date = today + timedelta(days=day_offset)
pillar = PILLARS[day_offset % len(PILLARS)]
platform = PLATFORMS[day_offset % len(PLATFORMS)]
hook = SEASONAL_HOOKS[day_offset % len(SEASONAL_HOOKS)] if day_offset < 3 else ""
rows.append({
"Day": day_offset + 1,
"Date": date.isoformat(),
"Platform": platform,
"Pillar": pillar,
"Topic": f"[{pillar}] — {CLIENT} {NICHE} content #{day_offset+1}",
"Hook/Format": hook or "Reel / Carousel / Single Image",
"CTA": "Shop now (link in bio)",
"Assets Needed": "Product photo, user UGC, or flat lay",
"Notes": BRAND_VOICE,
})
writer = csv.DictWriter(sys.stdout, fieldnames=HEADERS)
writer.writeheader()
writer.writerows(rows)
print(f"\n# Calendar for {CLIENT} — {today.strftime('%B %Y')}", file=sys.stderr)
print(f"# Generated: {len(rows)} posts across {len(PLATFORMS)} platforms", file=sys.stderr)
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 · 219 lines · 38 tokens per session scan A 2e29ae62622e
content-planner-auto is a skill published in the GitHub repository oyi77/1ai-skills (12 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 2,055 once invoked, about $0.0002 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 2026-09-03.
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