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.
git clone --depth 1 https://github.com/ghaida/intentWrote 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/rules/ghaida/intent/intent-ref-content-strategy)<a href="https://agentmods.dev/rules/ghaida/intent/intent-ref-content-strategy"><img src="https://agentmods.dev/badge/rules/ghaida/intent/intent-ref-content-strategy/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/rules/ghaida/intent/intent-ref-content-strategy"><img src="https://agentmods.dev/badge/rules/ghaida/intent/intent-ref-content-strategy.svg" alt="Reviewed on agentmods" width="80" 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 | $0.03225 | $0.03225 |
| Opus 5.5 | $0.01290 | $0.01290 |
| Sonnet 5.5 | $0.00645 | $0.00645 |
| Haiku 4.5 | $0.00323 | $0.00323 |
Grade A, and why
intent-ref-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 1mo 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 — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Strategy
Voice Framework Methodology
A voice framework is not a list of adjectives. It's a system that produces consistent, recognizable writing across every author, channel, and context in your product. Building one requires methodology, not inspiration.
Step 1: Brand Attribute Identification
Start with the brand's core attributes — the 3-5 characteristics that define how the organization wants to be perceived. These come from brand strategy, not from the content team's preferences.
Process: Gather stakeholders (product, marketing, executive, support). Ask each: "If our product were a person, how would you describe their personality?" Collect independently, then compare. Where there's alignment, you have a genuine attribute. Where there's divergence, you have a conversation that needs to happen before writing guidelines.
Common pitfall: Every brand wants to be "innovative, friendly, and trustworthy." These are not differentiating attributes — they're table stakes. Push for specificity. Not "friendly" — "the kind of friend who tells you the truth even when it's uncomfortable." Not "innovative" — "explains complex things simply, like a scientist at a dinner party."
Output: 3-5 brand attributes with one-paragraph descriptions that include what the attribute means AND what it doesn't mean. Example: "Direct — we get to the point. We don't pad copy with qualifiers or hide bad news behind hedging language. Direct does not mean blunt or cold — we're straightforward because we respect the reader's time, not because we don't care about their feelings."
Step 2: Voice Principles
Translate brand attributes into writing principles. Each attribute generates 1-2 specific principles that a writer can act on.
Attribute → Principle pattern:
- "Direct" → "Lead with the action. If the user needs to do something, start with the verb."
- "Empathetic" → "Acknowledge the user's situation before providing instructions. Error messages start with what happened, not what to do."
- "Expert" → "Use precise terminology when it helps, but always define it in context. Never use jargon as a substitute for explanation."
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.
- 1mo ago First seen · 234 lines · 3,225 tokens per session scan A b6e758fd8721
intent-ref-content-strategy is a cursor rule published in the GitHub repository ghaida/intent (214 stars, last pushed 7d ago), licensed CC0-1.0. It adds 3,225 tokens to every session, about $0.0129 per session on Opus 5.5. 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 2026-08-30.
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