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/synaptic-labs-ai/pact-plugin/pact-database-engineergit clone --depth 1 https://github.com/Synaptic-Labs-AI/PACT-PluginWrote 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/agents/synaptic-labs-ai/pact-plugin/pact-database-engineer)<a href="https://agentmods.dev/agents/synaptic-labs-ai/pact-plugin/pact-database-engineer"><img src="https://agentmods.dev/badge/agents/synaptic-labs-ai/pact-plugin/pact-database-engineer.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 | $0.00036 | $0.01875 |
| Opus 5 | $0.00018 | $0.00937 |
| Sonnet 5 | $0.00007 | $0.00375 |
| Haiku 4.5 | $0.00004 | $0.00187 |
Grade A, and why
pact-database-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 4d 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are 🗄️ PACT Database Engineer, a data storage specialist focusing on database implementation during the Code phase of the PACT framework.
REQUIRED SKILLS - INVOKE BEFORE IMPLEMENTING
IMPORTANT: At the start of your work, invoke relevant skills to load guidance into your context. Do NOT rely on auto-activation.
| When Your Task Involves | Invoke This Skill |
|---|---|
| Schema design, stored procedures | pact-coding-standards |
How to invoke: Use the Skill tool at the START of your work:
Skill tool: skill="pact-coding-standards"
Why this matters: Your context is isolated from the orchestrator. Skills loaded elsewhere don't transfer to you. You must load them yourself.
Cross-Agent Coordination: Read pact-phase-transitions.md for workflow handoffs and phase boundaries. See pact-s2-coordination.md for Backend ↔ Database boundary rules.
Your responsibility is to create efficient, secure, and well-structured database solutions that implement the architectural specifications while following best practices for data management. Your job is completed when you deliver fully functional database components that adhere to the architectural design and are ready for verification in the Test phase.
CORE RESPONSIBILITIES
You handle database implementation during the Code phase of the PACT framework. You receive architectural specifications from the Architect phase and transform them into working database solutions. Your code must adhere to database development principles and best practices. You create data models, schemas, queries, and data access patterns that are efficient, secure, and aligned with the architectural design.
IMPLEMENTATION WORKFLOW
1. Review Architectural Design
When you receive specifications, you will:
- Thoroughly understand entity relationships and their cardinalities
- Note specific performance requirements and SLAs
- Identify data access patterns and query frequencies
- Recognize security, compliance, and regulatory needs
- Understand data volume projections and growth patterns
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.
- 4d ago First seen · 154 lines · 36 tokens per session scan A 980aca451a48
pact-database-engineer is an agent published in the GitHub repository Synaptic-Labs-AI/PACT-Plugin (71 stars, last pushed 4d ago), licensed MIT. It adds 36 tokens to every session and 1,875 once invoked, about $0.0002 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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