ai-customization

ai-customization is a cursor rule for Cursor from lsampaioweb/ai-instructions. It costs 0 tokens per session (1,362 once invoked), scanned A, original, MIT.

Writing rules for organizing guidance used by Cursor and GitHub Copilot, which are coding assistants. It explains when to use project instructions, path-specific rules, reusable skills, prompts, and agent definitions.

In plain words
What is it for?
Use it when creating or reviewing AGENTS.md files, Cursor rules, Copilot instructions, prompt templates, and agent definitions.
Why use it?
It prevents guidance from being placed in the wrong file, repeated in several places, or written too vaguely for the assistant to apply reliably.

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/lsampaioweb/ai-instructions/ai-customization
Clone the repo
git clone --depth 1 https://github.com/lsampaioweb/ai-instructions

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 ai-customization

README.md
[![agentmods](https://agentmods.dev/badge/rules/lsampaioweb/ai-instructions/ai-customization.svg)](https://agentmods.dev/rules/lsampaioweb/ai-instructions/ai-customization)
Your own site
<a href="https://agentmods.dev/rules/lsampaioweb/ai-instructions/ai-customization"><img src="https://agentmods.dev/badge/rules/lsampaioweb/ai-instructions/ai-customization.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 1,362 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 $0.00000 $0.01362
Opus 5 $0.00000 $0.00681
Sonnet 5 $0.00000 $0.00272
Haiku 4.5 $0.00000 $0.00136

Measured 3d ago against content hash ab966d80f272, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ai-customization 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.

.cursor/rules/ai-customization.mdc · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Customization Style Contract

Pick the right artifact

Need Use Notes
Always-on project behavior Root AGENTS.md Plain markdown; no YAML frontmatter
Scoped guidance (paths, topics) .cursor/rules/*.mdc globs or alwaysApply; not for duplicating AGENTS.md
Repeatable workflow the user invokes .cursor/skills/**/SKILL.md YAML frontmatter + procedural body
Domain or stack guidance (path-scoped) .mdc with globs Copilot sources live under .github/instructions/
User-invoked Copilot task template *.prompt.md Frontmatter with description and argument-hint
Multi-step Copilot agent persona *.agent.md Copilot sources live under .github/agents/
  • Do not put global behavior in a rule if it belongs in AGENTS.md.
  • Do not duplicate the same rule across AGENTS.md, rules, and skills.

Rules

  • Keep frontmatter discoverable: description must state when to use the file.
  • Remove routing noise: avoid vague descriptors that do not improve file selection.
  • Use directive language: write mandatory rules with imperative verbs.
  • Keep optional behavior explicit: mark optional rules with an explicit optional tag.
  • Use one rule per bullet: each bullet must express one enforceable behavior.
  • Split compound bullets: break combined requirements into separate rules.
  • Keep sections purpose-specific: section title and rule scope must match.
  • Move off-topic rules: relocate unrelated content to a dedicated section.
  • Minimize low-signal wording: remove filler that does not change execution.
  • Shorten verbose statements: keep the same meaning with fewer words.
  • Preserve technical literals: do not alter commands, code, paths, URLs, identifiers, config keys, or versions unless incorrect.
  • Resolve duplication deliberately: keep one canonical statement and reference it from secondary files.
  • Resolve contradictions explicitly: define precedence or rewrite to remove conflict.
  • State each constraint once in the strongest clear polarity; do not restate a Rules bullet as its negation in Safety Guards or in the same bullet.
  • Do not append ; never … (or equivalent) inside a Rules bullet when that prohibition is already covered by the Must form or by Safety Guards.
  • Prefer one canonical file for cross-cutting policy; secondary files use a one-line deferral and must not copy the rule.
  • Before adding a preference: search for an existing rule covering the decision; merge or reference instead of appending. Add a rule only when it changes a default decision and does not duplicate an existing rule.

Read the full file on GitHub · 85 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. 3d ago First seen · 85 lines · 0 tokens per session scan A ab966d80f272

Subscribe to this mod's changes

ai-customization is a cursor rule published in the GitHub repository lsampaioweb/ai-instructions (1 stars, last pushed 11d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,362 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.