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/fatihkan/badi/content-plangit clone --depth 1 https://github.com/fatihkan/badiWrote 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/fatihkan/badi/content-plan)<a href="https://agentmods.dev/commands/fatihkan/badi/content-plan"><img src="https://agentmods.dev/badge/commands/fatihkan/badi/content-plan.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 | $0.00000 | $0.00743 |
| Opus 5 | $0.00000 | $0.00371 |
| Sonnet 5 | $0.00000 | $0.00149 |
| Haiku 4.5 | $0.00000 | $0.00074 |
Grade A, and why
content-plan 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 3d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly content planning session command. Sets next week's content strategy, themes, and production targets.
Required Tools
- Read (brand voice, past calendars, performance)
- Write (new calendar file)
- Grep (past content analysis)
- Glob (file search)
- Bash (date calculations)
Procedure (6 Steps)
Step 1: Last Week's Review
Analyze the last 7 days of production output:
- How much content was produced? (per platform)
- Which were planned, which spontaneous?
- Any planned content left unfinished?
- Which format do you produce most? (post, carousel, video)
Ask:
- What were your 3 best pieces? (by engagement or satisfaction)
- Which was the hardest? (why was it hard?)
Step 2: Next Week's Themes
Build the week's theme map:
Data sources:
- Special days and events (check the calendar)
- Seasonal opportunities
- Current topics (brand-fit)
- Ongoing campaigns
- Customer questions / FAQ
Set 1 main theme per day:
Monday: [theme] — [why]
Tuesday: [theme]
...
Step 3: Platform Distribution
Set a weekly target per platform:
| Platform | Format | Target Count | Theme Link |
|---|---|---|---|
| Instagram Post | ... | ... | ... |
| Instagram Reel | ... | ... | ... |
| Twitter/X | ... | ... | ... |
| ... | ... | ... | |
| TikTok | ... | ... | ... |
Note: 3-5 items per platform is enough (quality > quantity).
Step 4: Build the Content Matrix
Clear planning per day and platform:
Monday:
- IG Post: "[topic]" (theme: [theme])
- Twitter: thread "[topic]"
Tuesday:
- IG Reel: 30s "[topic]"
- LinkedIn: "[topic]"
...
Step 5: Production Cadence
Plan when you will produce the content:
- Batch production day (example: Monday morning for the whole week)
- Daily production (each day for that day)
- Mixed model (prepared ahead + current)
Tip: batch production is efficient, but topical content keeps things dynamic.
Step 6: Save the Calendar File
Create the detailed file with the /content-calendar command, or suggest the
badi content calendar "[week-date]" CLI command.
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.
- 3d ago First seen · 137 lines · 0 tokens per session scan A 93808f40ddab
content-plan is a command published in the GitHub repository fatihkan/badi (7 stars, last pushed 17d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 743 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.
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