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/niksacdev/engineering-team-agents/agents-mdgit clone --depth 1 https://github.com/niksacdev/engineering-team-agentsWhat 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 | $0.01196 | $0.01196 |
| Opus 5 | $0.00598 | $0.00598 |
| Sonnet 5 | $0.00239 | $0.00239 |
| Haiku 4.5 | $0.00120 | $0.00120 |
Grade A, and why
engineering-team-agents AGENTS.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 2d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Project: Collaborative Engineering Team Agents
Enterprise-grade multi-agent system for reliable, maintainable, and business-aligned code.
Agent Collaboration Pattern
Every feature request follows this collaborative workflow:
- Product Manager clarifies user needs and business value
- UX Designer maps user journeys and validates workflows
- Architecture ensures scalable, secure system design
- Code Reviewer validates implementation quality and security
- Technical Writer creates documentation and content
- Responsible AI prevents bias and ensures accessibility
- GitOps optimizes deployment and operational excellence
All agents create persistent documentation in structured docs/ folders.
Available Specialists
Product Management Agent
- Role: Clarifies requirements, validates business value
- Outputs: Requirements documents, GitHub issues, user stories
- Location: Product-focused development guidance
- Collaboration: Partners with UX Designer for user journey mapping
Architecture Reviewer Agent
- Role: Validates system design, creates technical decisions
- Outputs: Architecture Decision Records (ADRs), system design docs
- Location: Enterprise architecture guidance
- Collaboration: Consults Code Reviewer for security implications
Code Quality Agent
- Role: Security-first code review, quality validation
- Outputs: Code review reports with specific fixes
- Location: Enterprise security and quality standards
- Collaboration: Escalates architectural concerns to Architecture Agent
UX Design Agent
- Role: User journey mapping, accessibility validation
- Outputs: User journey maps, accessibility compliance reports
- Location: User experience and accessibility guidance
- Collaboration: Validates business impact with Product Manager
Technical Writer Agent
- Role: Documentation creation, content writing, tutorials
- Outputs: Blogs, tutorials, API docs, ADRs, technical guides
- Location: Technical writing and documentation guidance
- Collaboration: Works with Product Manager for requirements clarity
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.
- 2d ago First seen · 131 lines · 1,196 tokens per session scan A ecd6fb4ddfe2
engineering-team-agents AGENTS.md is an instructions file published in the GitHub repository niksacdev/engineering-team-agents (47 stars, last pushed 1mo ago), licensed MIT. It adds 1,196 tokens to every session, about $0.0060 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 2026-08-30.
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