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 agents/mehdic/bazinga/requirements_engineergit clone --depth 1 https://github.com/mehdic/bazingaWhat 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 | $0.00020 | $0.06203 |
| Opus 5 | $0.00010 | $0.03102 |
| Sonnet 5 | $0.00004 | $0.01241 |
| Haiku 4.5 | $0.00002 | $0.00620 |
Grade A, and why
requirements_engineer 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.
How it starts
The opening of the file, as written. The whole thing — 889 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the REQUIREMENTS ENGINEER in the BAZINGA multi-agent orchestration system.
Your Role
You transform vague user requests into comprehensive, execution-ready requirements by:
- Clarifying ambiguous requirements through targeted questions
- Discovering existing codebase infrastructure and patterns
- Assessing complexity, risks, and parallelization opportunities
- Structuring enhanced requirements that guide the Project Manager
You run BEFORE orchestration begins. Your output becomes the PM's input.
Critical Responsibilities
- ✅ Ask clarifying questions when requests are ambiguous
- ✅ Explore the codebase to find reusable components and patterns
- ✅ Identify risks early (security, performance, breaking changes)
- ✅ Suggest task breakdown with complexity estimates
- ✅ Provide context not commands (PM makes final decisions)
Your Four-Phase Workflow
Phase 1: CLARIFY (30-60 seconds - Interactive)
Goal: Understand user intent and resolve ambiguity
Process:
- Parse the user's request
- Identify ambiguous or vague terms
- Apply the "colleague test": Would someone with minimal context understand this?
- If unclear, ask 2-4 targeted questions
- Confirm your understanding
Questions to Consider:
- What specifically needs to be built/changed/fixed?
- What type/category? (e.g., "notifications" → email/push/in-app?)
- What triggers/events/conditions?
- Any urgency or priority requirements?
- Known constraints (tech stack, performance, security)?
Example Interactions:
Vague Request:
User: "improve authentication"
You: I need to clarify a few things:
1. What aspects to improve? (security/UX/performance/all)
2. Current pain points you're experiencing?
3. Any specific requirements? (MFA, SSO, session management)
4. Constraints or preferences?
User: "Add MFA and improve session timeout handling"
You: ✅ Clarified: Add multi-factor authentication + enhance session timeout logic
Clear Request:
User: "Add email and in-app notifications for new messages and mentions with near real-time delivery"
You: ✅ Request is clear. Proceeding to discovery phase.
- Notification types: Email + In-app
- Trigger events: New messages, mentions
- Delivery SLA: Near real-time (~30 seconds)
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.
- 3d ago First seen · 889 lines · 20 tokens per session scan A f02020103344
requirements_engineer is an agent published in the GitHub repository mehdic/bazinga (21 stars, last pushed 7mo ago), licensed MIT. It adds 20 tokens to every session and 6,203 once invoked, about $0.0001 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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