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/markmhendrickson/foundationWrote 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/markmhendrickson/foundation/content_style_enforcement)<a href="https://agentmods.dev/rules/markmhendrickson/foundation/content_style_enforcement"><img src="https://agentmods.dev/badge/rules/markmhendrickson/foundation/content_style_enforcement/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/markmhendrickson/foundation/content_style_enforcement"><img src="https://agentmods.dev/badge/rules/markmhendrickson/foundation/content_style_enforcement.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 | $0.00030 | $0.01247 |
| Opus 5.5 | $0.00012 | $0.00499 |
| Sonnet 5.5 | $0.00006 | $0.00249 |
| Haiku 4.5 | $0.00003 | $0.00125 |
Grade A, and why
content_style_enforcement 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Style Enforcement Rule
Reference: foundation/conventions/writing_style_guide.md — Writing style guide
Ensures all content (essays, articles, posts, documentation) always follows anti-AI patterns and authentic human voice standards.
Trigger Patterns
When creating or editing ANY content:
- Essays, articles, blog posts
- Social media content
- Documentation
- Marketing copy
- Technical writing
- Any written content for publication
Agent Actions
Step 1: Load Style Guide
Before finalizing any content:
- Load
foundation/conventions/writing_style_guide.md - Review prohibited patterns
- Apply all style rules
Step 2: Apply Anti-AI Patterns
Before finalizing any content, MUST remove all AI-generated language patterns per the writing style guide:
Generic AI Phrases to Remove:
- "Furthermore", "Moreover", "In addition"
- "leverage" → use "use" or "draw on"
- "empower" → use "enable" or "let"
- "cutting-edge" → use specific technical terms
- "revolutionary", "game-changing", "seamless" → remove marketing hype
Corporate Speak to Reduce:
- "solution" → use specific description
- "platform" → use "tool" or "system" where appropriate
- "ecosystem" → use only when necessary, prefer specific names
Language Simplification:
- "utilize" → "use"
- "facilitate" → "enable" or "help"
- "remembrances" → "memories"
- "structural foundation" → "foundation"
- Passive voice → Active voice ("it was found" → "I found")
Punctuation Patterns (AI-Generated Tendencies):
- NEVER use em dashes (—) or en dashes (–)
- Use commas for appositives and lists
- Use periods to separate ideas
- Use colons to introduce lists or explanations
- Use standard hyphens (-) for compound words and ranges
Conversational Transitions (AI-Generated Tendencies):
- NEVER use: "Now, let's...", "So, you might...", "Interestingly...", "As you can see...", "Keep in mind that..."
- Use direct statements without transition words
- Start with the subject directly
Soft Questions and Offers (AI-Generated Tendencies):
- NEVER use: "Would you like to...?", "Have you considered...?", "Want to try...?", "Need help with...?"
- Use direct instructions: "Use the
store_recordaction to..." - Use declarative statements: "The system supports..."
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 · 138 lines · 30 tokens per session scan A 91238cbf9996
content_style_enforcement is a cursor rule published in the GitHub repository markmhendrickson/foundation (2 stars, last pushed 2mo ago), licensed MIT. It adds 30 tokens to every session and 1,247 once invoked, about $0.0001 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 2026-08-31.
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