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 skills/sjarmak/agent-workflows/stress-testnpx skills add sjarmak/agent-workflows --skill stress-testgit clone --depth 1 https://github.com/sjarmak/agent-workflowsWrote 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/skills/sjarmak/agent-workflows/stress-test)<a href="https://agentmods.dev/skills/sjarmak/agent-workflows/stress-test"><img src="https://agentmods.dev/badge/skills/sjarmak/agent-workflows/stress-test.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 | $0.00000 | $0.01862 |
| Opus 5 | $0.00000 | $0.00931 |
| Sonnet 5 | $0.00000 | $0.00372 |
| Haiku 4.5 | $0.00000 | $0.00186 |
Grade A, and why
stress-test 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 6d 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel Adversarial Attack Surface Analysis. Spawns N independent agents, each tasked with BREAKING a system from a different attack angle. No agent sees others' findings. Synthesizes into a vulnerability map with severity ratings.
Arguments
$ARGUMENTS — format: [N] [path/to/code_or_design or inline description] where N is optional (default: 5, min 3, max 7)
Parse Arguments
Extract:
- agent_count: the optional leading integer (default 5, min 3, max 7)
- attack_target: the file path, directory path, or inline description of the system to analyze
If the target is missing or unclear, ask the user to clarify before proceeding.
Phase 1: Identify the Target
Determine the target type and build a comprehensive understanding:
- If a file or directory path is given: read and explore it to understand the system — its structure, components, dependencies, data flows, trust boundaries, and deployment model
- If an inline description is given: parse it for the same information
Prepare a target brief covering:
- What the system does (purpose, scope)
- Components and their responsibilities
- Dependencies (internal and external)
- Data flows (input sources, processing, storage, output)
- Trust boundaries (authenticated vs unauthenticated, internal vs external, admin vs user)
- Deployment model (where it runs, how it scales)
Present the target brief to the user and confirm before proceeding. Adjust if the user gives feedback.
Phase 2: Spawn Attack Agents
Launch all N agents in parallel using the Agent tool. Each agent gets the target brief plus a unique attack vector selected from this list (assign sequentially, wrapping if N < 7):
Attack Vector 1: Edge Cases & Input Boundaries
Malformed input, boundary values, type confusion, unicode edge cases, empty/null/huge payloads, concurrent conflicting inputs, format string attacks, deserialization of untrusted data.
Attack Vector 2: Scale & Resource Exhaustion
What happens at 100x load, memory leaks under sustained use, unbounded growth (queues, logs, caches), connection pool exhaustion, hot spots, thundering herd, algorithmic complexity attacks (ReDoS, hash collision).
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.
- 6d ago First seen · 172 lines · 0 tokens per session scan A a8191ba99c25
stress-test is a skill published in the GitHub repository sjarmak/agent-workflows (9 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,862 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.
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