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 yogsoth-ai/stress-test --skill systematic-probinggit clone --depth 1 https://github.com/yogsoth-ai/stress-testWrote 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/yogsoth-ai/stress-test/systematic-probing)<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/systematic-probing"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/systematic-probing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/systematic-probing"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/systematic-probing.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00036 | $0.00713 |
| Opus 5 | $0.00018 | $0.00357 |
| Sonnet 5 | $0.00007 | $0.00143 |
| Haiku 4.5 | $0.00004 | $0.00071 |
Grade A, and why
systematic-probing 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 7d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Probing Strategy
Anthropic-style systematic probing: exhaustive coverage of all threat surfaces with structured attack generation and execution.
Method
- threat-surface-mapping enumerates all attackable surfaces of the artifact
- attack-vector-generation produces specific attacks per surface
- Vectors prioritized by expected severity and likelihood
- probe-execution executes each attack, records success/failure/partial
- Failed probes trigger deeper investigation via follow-up vectors
- attack-resilience-scoring computes coverage and resilience metrics
Budget Table
| Parameter | S | M | L |
|---|---|---|---|
| Attack vectors | 5 | 12 | 20 |
| Probing rounds | 3 | 6 | 10 |
| Personas | 2 | 4 | 6 |
| Assumption checks | 5 | 10 | 20 |
Orchestration
threat-surface-mapping → [enumerate surfaces]
→ [for each surface]:
attack-vector-generation (generate vectors)
→ [for each vector]:
probe-execution (execute attack)
→ (if partial success: generate follow-up vectors)
→ finding-aggregation → attack-resilience-scoring
Subagents
- threat-surface-mapping (surface enumeration)
- attack-vector-generation (vector design)
- probe-execution (attack execution)
- finding-aggregation (result synthesis)
- attack-resilience-scoring (metric computation)
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use |
|---|---|
| assumption-cascade | Tactic: Surface assumptions, sort by dependency, attack root assumptions first, then trace cascade failures through the dependency graph. |
| structured-attack-campaign | Tactic: Full attack lifecycle — threat surface enumeration, attack vector generation, systematic probing, and finding aggregation across all surfaces. |
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| attack-resilience-scoring | Compute overall resilience score (0.0-1.0) based on attack results, coverage, and vulnerability severity distribution. |
| attack-vector-generation | Generate specific attack strategies for a given threat surface, producing concrete probes that can be executed. |
| finding-aggregation | Aggregate, deduplicate, and classify findings from multiple probes into a coherent vulnerability report. |
| probe-execution | Execute a single attack probe against an artifact, record the result with evidence and severity classification. |
| threat-surface-mapping | Enumerate all attackable surfaces of an artifact — logical, empirical, methodological, social, and practical dimensions. |
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.
- 7d ago First seen · 88 lines · 36 tokens per session scan A 0f5dfa0bf6db
systematic-probing is a skill published in the GitHub repository yogsoth-ai/stress-test (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 36 tokens to every session and 713 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 2026-09-03.
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