content-strategy

content-strategy is a cursor rule for Cursor from rajitsaha/100xprism. It costs 31 tokens per session (2,187 once invoked), scanned A, original, MIT.

A set of guidelines for deciding what content to create and how it should support a business goal.

In plain words
What is it for?
Use it to plan blogs, topic groups, and other searchable or shareable content.
Why use it?
It helps avoid publishing random topics by connecting content to customer questions, search demand, and available resources.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/rajitsaha/100xprism/content-strategy
Clone the repo
git clone --depth 1 https://github.com/rajitsaha/100xprism

Made for: Cursor.

Wrote 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.

agentmods badge for content-strategy

README.md
[![agentmods](https://agentmods.dev/badge/rules/rajitsaha/100xprism/content-strategy.svg)](https://agentmods.dev/rules/rajitsaha/100xprism/content-strategy)
Your own site
<a href="https://agentmods.dev/rules/rajitsaha/100xprism/content-strategy"><img src="https://agentmods.dev/badge/rules/rajitsaha/100xprism/content-strategy.svg" alt="Measured on agentmods" height="20"></a>
Per session 31 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,187 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00031 $0.02187
Opus 5 $0.00015 $0.01094
Sonnet 5 $0.00006 $0.00437
Haiku 4.5 $0.00003 $0.00219

Measured today against content hash e48473aa891c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

content-strategy 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 today.

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.

.cursor/rules/content-strategy.mdc · 221 lines

How it starts

The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Strategy

Plan content that drives traffic, builds authority, and generates leads by being searchable, shareable, or both.

Before Planning

Product context: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it first and tailor output to it; only ask for what it doesn't cover.

Gather (ask if not provided):

  1. Business Context — what the company does; ideal customer; problems the product solves; primary content goal (traffic, leads, brand awareness, thought leadership)
  2. Customer Research — questions customers ask before buying; objections in sales calls; recurring support-ticket topics; the language customers use for their problems
  3. Current State — existing content and what's working; resources (writers, budget, time); producible formats (written, video, audio)
  4. Competitive Landscape — main competitors; content gaps in the market

Searchable vs Shareable

Every piece must be searchable, shareable, or both — prioritize in that order; search traffic is the foundation. Searchable content captures existing demand from people actively looking for answers. Shareable content creates demand by spreading ideas.

Searchable: target a specific keyword or question and match search intent exactly; clear titles matching search queries; headings that mirror search patterns; keywords in title, headings, first paragraph, URL; comprehensive coverage (leave no questions unanswered) with data, examples, links to authoritative sources; optimize for AI/LLM discovery (clear positioning, structured content, brand consistency across the web).

Shareable: lead with a novel insight, original data, or counterintuitive take; challenge conventional wisdom with well-reasoned arguments; tell stories that make people feel something; share vulnerable, honest experiences others can learn from; create content people share to look smart or help others; connect to current trends or emerging problems.

Read the full file on GitHub · 221 lines

Changes

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.

  1. today First seen · 221 lines · 31 tokens per session scan A e48473aa891c

Subscribe to this mod's changes

content-strategy is a cursor rule published in the GitHub repository rajitsaha/100xprism (10 stars, last pushed 4d ago), licensed MIT. It adds 31 tokens to every session and 2,187 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.