Borrowing it
Nothing to install: this file belongs to govindgoel2001/content-os-template. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/govindgoel2001/content-os-template/main/CLAUDE.mdgit clone --depth 1 https://github.com/govindgoel2001/content-os-templateWrote 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/instructions/govindgoel2001/content-os-template/claude-md)<a href="https://agentmods.dev/instructions/govindgoel2001/content-os-template/claude-md"><img src="https://agentmods.dev/badge/instructions/govindgoel2001/content-os-template/claude-md.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 5.1 | $0.00723 | $0.00723 |
| Opus 5 | $0.00362 | $0.00362 |
| Sonnet 5 | $0.00145 | $0.00145 |
| Haiku 4.5 | $0.00072 | $0.00072 |
Grade A, and why
content-os-template CLAUDE.md 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content OS — rules for AI sessions
This folder is an Obsidian vault and the operating system for my content brand. Goal: grow the audience, make money from it, and turn what I learn into teachable material.
Identity
- Brand: @your_handle — your niche one-liner
- Pillars: e.g. 40% Pillar A · 30% Pillar B · 20% Pillar C · 10% Pillar D (revisit with data monthly)
- Funnel: post → comment keyword → autodm (link) → free value → community / products
Topic ledgers + the self-improving loop (core mechanic)
Topics/<Lane>/STATE.mdis the context ledger per vertical. Before producing ANY content in a lane, read its STATE.md. After results come in, append a retro line (date · what worked · what to change) and update its scoreboard. This is how run 10 beats run 1 — never produce lane content from a cold start.Analytics/Diagnostics.mdtracks craft/falloff (hooks, pacing, retention). One hypothesis tested per week; verdicts recorded at weekly review.
Session behavior
- Every session that produces an insight, idea, draft, or result writes a note into the vault. The vault must grow. Use
[[wikilinks]]between notes. - New content ideas →
Pipeline/Ideas.md. Approved/scheduled →Pipeline/Queue.md. After posting, move the entry toPipeline/Posted.mdwith date + format + hook. - When asked "what should I post": read
Analytics/What-Is-Working.md+ latestResearch/note first, then propose fromPipeline/Ideas.mdor generate new ideas grounded in what's working. Never propose blind. - Trend research: use the
/last30daysskill; save the output asResearch/YYYY-MM-DD-<topic>.md. - Analytics pulls: Apify scrape for competitor + own-account engagement; Composio MCP for Instagram insights + YouTube analytics; write findings into
Analytics/. - Monetization questions: ground answers in
Monetization/Money-Map.md; update it when the funnel changes. - Learning loop: when I learn something new (a workflow, MCP, automation), add it to
Learning/Learn-Next.mdand flag whether it's course-worthy →Learning/Course-Pipeline.md.
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 · 45 lines · 723 tokens per session scan A a2623765ab14
content-os-template CLAUDE.md is an instructions file published in the GitHub repository govindgoel2001/content-os-template (2 stars, last pushed 1mo ago), licensed MIT. It adds 723 tokens to every session, about $0.0036 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.
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