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.
npx agentmods add instructions/lsampaioweb/ai-instructions/ai-customizationgit clone --depth 1 https://github.com/lsampaioweb/ai-instructionsWrote 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/lsampaioweb/ai-instructions/ai-customization)<a href="https://agentmods.dev/instructions/lsampaioweb/ai-instructions/ai-customization"><img src="https://agentmods.dev/badge/instructions/lsampaioweb/ai-instructions/ai-customization.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 | $0.00861 | $0.00861 |
| Opus 5 | $0.00430 | $0.00430 |
| Sonnet 5 | $0.00172 | $0.00172 |
| Haiku 4.5 | $0.00086 | $0.00086 |
Grade A, and why
ai-instructions ai-customization.instructions.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 yesterday.
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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Customization Style Contract
Rules
- Keep frontmatter discoverable:
descriptionmust state when to use the file. - Keep prompt frontmatter explicit:
argument-hintmust state required input. - 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.
Instruction File Rules
- Set
applyToto the most specific glob pattern that covers the target files without over-matching. - Use this canonical section order for engine instruction files:
## Dependencies(if applicable),## Naming Conventions(if applicable),## Rules,## Approved Exception Handling(if applicable),## Safety Guards(if applicable). - Omit
## Scope & Analysisand## Review Plan Layoutfrom engine instruction files. - Use
## Dependenciesonly for real Maven/starter requirements or essential cross-topic deferrals; do not list files already activated byapplyToor architecture intent references. - Omit
## Safety Guardswhen empty; if present, each bullet must forbid a behavior not already implied by Rules (asymmetric / high-cost prohibitions only: irreversible ops, security footguns, common agent failure modes, scope-creep bans). - Keep
## Approved Exception Handlingonly when temporary exceptions are a first-class protocol for that domain; put design alternatives in Rules. - Order rules within each section to match the top-to-bottom structure of the governed file.
- Place rules about elements that appear earlier in the target file before rules about elements that appear later.
- Keep durable false-positive dismissals for code-vs-instruction reviews in
.github/instructions/review-suppressions.instructions.md; prefer narrowing the cited instruction or domain Approved Exception Handling before adding a suppression row. - Require every Active Suppressions row to include stable
SUP-NNNID, Path, Rule citation, Reason, Owner, Expiry (YYYY-MM-DD), and Status (active|expired).
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.
- yesterday First seen · 50 lines · 861 tokens per session scan A 2e8cd57d434d
ai-instructions ai-customization.instructions.md is an instructions file published in the GitHub repository lsampaioweb/ai-instructions (1 stars, last pushed 12d ago), licensed MIT. It adds 861 tokens to every session, about $0.0043 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.
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