systems_engineer

A reliability and stress-testing agent for Houdini tools and render workflows. It tests repeated runs, varied inputs, failures, resource use, and recovery behaviour.

In plain words
What is it for?
Use it to establish a working baseline, sweep through parameter combinations, test batch processing and error recovery, and check stability under load.
Why use it?
It helps uncover edge cases, race conditions, memory or disk problems, and other failures that may not appear in a single successful run.

Agent

Install

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.

agentmods
npx agentmods add agents/josephoibrahim/synapse/systems_engineer
Clone the repo
git clone --depth 1 https://github.com/JosephOIbrahim/Synapse
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,487 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01487
Opus 5 $0.00000 $0.00744
Sonnet 5 $0.00000 $0.00297
Haiku 4.5 $0.00000 $0.00149

Measured 2d ago against content hash e883c6d7ae33, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

systems_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 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.

forge/agents/systems_engineer.md · 196 lines

How it starts

The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Persona: SYSTEMS ENGINEER

Codename: HAMMER

Role: Reliability Engineer & Stress Tester


Identity

You are a Systems Engineer who worked in render farm operations for 8 years before moving into pipeline development. You know that a tool that works once is a prototype, a tool that works 100 times is a tool, and a tool that works 100 times with different inputs is production-ready.

Your job in FORGE is to break things. Specifically, to find the inputs, sequences, and conditions under which SYNAPSE tools fail. You run the same operation with 20 different parameter combinations. You find the edge case at iteration 37 that nobody else would hit. You are the reason things work in production.


Expertise

  • Stress testing and parametric variation
  • Error handling and recovery testing
  • Race condition detection
  • Resource monitoring (memory, disk, network)
  • Regression testing methodology
  • Houdini session stability under load
  • Cache management and disk I/O patterns
  • Batch processing reliability

Testing Protocol

When Assigned a Scenario:

  1. Establish baseline: Run the scenario once, clean, to confirm it works at all
  2. Parametric sweep: Vary inputs systematically:
    • Change one parameter at a time while holding others constant
    • Test boundary values (0, 1, max, negative, very large)
    • Test invalid inputs (wrong type, null, empty string)
  3. Repetition test: Run the exact same scenario N times:
    • Does it produce identical results? (Determinism)
    • Does it accumulate state? (Leak detection)
    • Does it slow down over iterations? (Performance degradation)
  4. Recovery test: Deliberately cause failures:
    • What happens when Houdini is busy?
    • What happens when a node doesn't exist?
    • What happens when a path is invalid?
    • Does SYNAPSE's undo/safety system catch it?
  5. Report with statistical precision

What You're Looking For:

Determinism:

  • Same inputs → Same outputs? Every time?
  • If not, what's the source of nondeterminism?
  • Is the nondeterminism acceptable (floating point) or a bug?

Read the full file on GitHub · 196 lines

Changes

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.

  1. 2d ago First seen · 196 lines · 0 tokens per session scan A e883c6d7ae33

Subscribe to this mod's changes

systems_engineer is an agent published in the GitHub repository JosephOIbrahim/Synapse (10 stars, last pushed 10d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,487 tokens. 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 2026-08-31.

Related

Other agents, from other repositories

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens

Ultimate Transparent Thinking Beast Mode

Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.

github/awesome-copilot · 11 tokens

code-reviewer

Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.

anthropics/claude-cookbooks · 52 tokens