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/rjmurillo/ai-agents/unified-software-engineeringgit clone --depth 1 https://github.com/rjmurillo/ai-agentsWrote 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/rjmurillo/ai-agents/unified-software-engineering)<a href="https://agentmods.dev/instructions/rjmurillo/ai-agents/unified-software-engineering"><img src="https://agentmods.dev/badge/instructions/rjmurillo/ai-agents/unified-software-engineering.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 | $0.01447 | $0.01447 |
| Opus 5 | $0.00724 | $0.00724 |
| Sonnet 5 | $0.00289 | $0.00289 |
| Haiku 4.5 | $0.00145 | $0.00145 |
Grade A, and why
ai-agents unified-software-engineering.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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unified Software Engineering
This rule resolves conflicts between engineering principles that models already know (Clean Code, DDD, Refactoring, Pragmatic Programmer, Code Complete) so that contradictions do not produce inconsistent agent behavior. Use it as a tiebreaker and as a concrete blocklist when reviewing or generating code.
Cherry-picked from agent-rules-books (MIT). The full upstream document is intentionally not imported. Adding the entire 46KB rule set duplicates content already known to the model and degrades response quality.
Primary Directive
When uncertain, choose the option that makes the system easier to understand, safer to change, and more honest about its real constraints.
Prefer designs that:
- reduce the number of facts a reader must hold at once
- put each business rule in one authoritative place
- keep volatile details behind stable boundaries
- make data ownership and consistency explicit
- survive partial failure, retries, and operational stress
- preserve behavior during structural change
- shorten feedback loops
Reject designs that merely appear simpler by hiding complexity in callers, frameworks, databases, global state, queues, or operational assumptions.
Conflict Resolution Rules
Apply these rules when engineering principles appear to disagree.
Simplicity vs Rich Modeling
- Use the simplest design that honestly represents the problem.
- Simple CRUD or administrative workflows may use transaction scripts or simple service-layer code.
- Complex business rules, lifecycles, invariants, and language distinctions require richer domain modeling.
- Do not use DDD patterns as ceremony in generic or low-complexity subdomains.
- Do not flatten real domain complexity into passive records and procedural services.
Small Functions vs Deep Modules
- Functions and routines should be cohesive and understandable.
- Prefer small units when they clarify intent, isolate responsibility, or simplify testing.
- Avoid chains of tiny pass-through functions that force readers to jump constantly.
- A module may contain internal complexity when its public interface is small, meaningful, and stable.
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 · 138 lines · 1,447 tokens per session scan A 033f0f95b72c
ai-agents unified-software-engineering.instructions.md is an instructions file published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed today), licensed MIT. It adds 1,447 tokens to every session, about $0.0072 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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