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 proffesor-for-testing/agentic-qe --skill context-driven-testinggit clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote 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/proffesor-for-testing/agentic-qe/context-driven-testing)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/context-driven-testing"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/context-driven-testing/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/proffesor-for-testing/agentic-qe/context-driven-testing"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/context-driven-testing.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 | $0.00042 | $0.01224 |
| Opus 5.5 | $0.00017 | $0.00490 |
| Sonnet 5.5 | $0.00008 | $0.00245 |
| Haiku 4.5 | $0.00004 | $0.00122 |
Grade A, and why
context-driven-testing 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- context-driven-testing — 92% identical, 42 lines differ
How it starts
The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context-Driven Testing
<default_to_action> When making testing decisions or adapting approaches:
- ANALYZE context: project goals, constraints, risks, team skills
- QUESTION practices: "Why this? What risk does it address? What's the cost?"
- INVESTIGATE not just check: Does software solve the problem, or create new ones?
- ADAPT approach based on context, not "best practices"
- DOCUMENT discoveries, not pre-written plans
Quick Context Analysis:
- Mission: "Find important problems fast enough to matter" (not "execute test cases")
- Risk: Safety-critical = high rigor; internal tool = lighter touch
- Constraints: Startup with tight timeline ≠ enterprise with compliance
- Skills: Novice needs structure; expert adapts intuitively
Critical Success Factors:
- No "best practices" work everywhere - only good practices in context
- Testing is investigation, not script execution
- Context changes; your approach should too </default_to_action>
Quick Reference Card
When to Use
- Making testing decisions for new project
- Questioning "that's how it's done" dogma
- Adapting approach to specific constraints
- Exploratory testing sessions
RST Heuristics
| Heuristic | Application |
|---|---|
| SFDIPOT | Structure, Function, Data, Interfaces, Platform, Operations, Time |
| Oracles | Consistency with history, similar products, expectations, docs |
| Tours | Business District, Historical, Bad Neighborhood, Tourist, Museum |
Context-Driven Decisions
Example: Test Automation Level
Startup Context:
- Small team, rapid changes, unclear product-market fit
- Decision: Light automation on critical paths, heavy exploratory
- Rationale: Requirements change too fast for extensive automation
Enterprise Context:
- Stable features, regulatory requirements, large team
- Decision: Comprehensive automated regression suite
- Rationale: Stability allows automation investment to pay off
Example: Documentation
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 · 158 lines · 42 tokens per session scan A e95df1b33634
context-driven-testing is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (505 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 1,224 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-11.
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