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 skills add ai-analyst-lab/ai-analyst-plugin --skill stress-testgit clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-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/skills/ai-analyst-lab/ai-analyst-plugin/stress-test)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/stress-test"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/stress-test.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 89 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00093 | $0.02681 |
| Opus 5 | $0.00046 | $0.01340 |
| Sonnet 5 | $0.00019 | $0.00536 |
| Haiku 4.5 | $0.00009 | $0.00268 |
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 8d 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 — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Stress Test
Type: Standalone — reviews any analysis plan for methodological flaws
Purpose
Takes an analysis plan, investigation design, or analytical approach and pressure-tests it for hidden flaws — wrong baselines, survivorship bias, missing segments, uncontrolled confounds, and absent kill criteria. Acts as a "senior data scientist code review" for your analytical thinking.
This skill is standalone — it works on any analysis plan, whether produced by /analysis-design, written by the user, or pulled from an existing document.
When to Use
- Before committing a week to executing an analysis plan
- Before presenting an analysis design to stakeholders
- When you've written an analysis brief and want a gut-check
- When reviewing someone else's analytical approach
- After an analysis came back with unexpected results (was the design flawed?)
Inputs
| Input | Required | Source | Description |
|---|---|---|---|
{{PLAN}} |
Yes | User or file path | The analysis plan to review. Can be a file path, pasted text, or a description of the approach |
{{CONTEXT}} |
No | User | Business context — what decision this analysis will inform |
{{AUDIENCE}} |
No | User | Who will consume the results (affects what counts as "fatal" vs. "nice to have") |
{{DATA_DESCRIPTION}} |
No | User | Description of available data, if not obvious from the plan |
The 7-Point Stress Test
CRITICAL FIRST STEP: Check data availability BEFORE methodology review.
Before reviewing methodology quality, immediately verify that required data exists:
- Read the active dataset schema (
.knowledge/datasets/{active}/schema.md) - Check if the plan's required fields/tables/dimensions exist in the dataset
- If ANY required data is missing → HALT, skip checkpoints 1-6, jump straight to checkpoint 7, assign FAIL verdict with BLOCKER status, provide F grade, and stop
- If all required data exists → proceed with checkpoints 1-7 in order
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.
- 8d ago First seen · 274 lines · 93 tokens per session scan A c8275170bbe2
stress-test is a skill published in the GitHub repository ai-analyst-lab/ai-analyst-plugin (32 stars, last pushed 12d ago), licensed MIT. It adds 93 tokens to every session and 2,681 once invoked, about $0.0005 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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