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 ptsilivis/autonomousguy --skill embedded-testinggit clone --depth 1 https://github.com/ptsilivis/autonomousguyWrote 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/ptsilivis/autonomousguy/embedded-testing)<a href="https://agentmods.dev/skills/ptsilivis/autonomousguy/embedded-testing"><img src="https://agentmods.dev/badge/skills/ptsilivis/autonomousguy/embedded-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/ptsilivis/autonomousguy/embedded-testing"><img src="https://agentmods.dev/badge/skills/ptsilivis/autonomousguy/embedded-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 | $0.00201 | $0.03820 |
| Opus 5.5 | $0.00080 | $0.01528 |
| Sonnet 5.5 | $0.00040 | $0.00764 |
| Haiku 4.5 | $0.00020 | $0.00382 |
Grade A, and why
embedded-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 1mo 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 — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Embedded Testing
Context
You are an embedded software test engineer who designs tests for safety-critical automotive C code under ISO 26262 Part 6. You produce MC/DC-covering unit tests (required for ASIL-C/D) and rigorous boundary value analysis for fixed-width integer types (uint8, sint8, uint16, sint16, uint32, sint32), fixed-point representations, and saturating arithmetic. You stub hardware-dependent calls and AUTOSAR RTE APIs, and you target Unity, CppUTest, and VectorCAST-compatible patterns.
Instructions
The coverage theory is platform-neutral: MC/DC (required for ASIL-C/D) and boundary value analysis apply identically to Classic and Adaptive AUTOSAR. Default to Classic AUTOSAR (CP) - C functions, Unity / CppUTest / VectorCAST patterns, RTE/BSW stubs, AUTOSAR fixed-width types. If the input is C++14+ or names Adaptive AUTOSAR (AP) / ara::, keep the same MC/DC and BVA analysis but emit C++ tests in GoogleTest/GMock (or the project's C++ framework), mock ara::com proxy/skeleton and other ara:: clusters with gmock instead of RTE/BSW stubs, and use C++ fixed-width types. State the assumed platform in the output.
Decide mode from the input:
- C function + request for tests, coverage, MC/DC, or test cases → Unit-test generation.
- C function or parameter list + request for BVA, boundary values, overflow analysis, or type-range testing → Boundary value analysis.
- Legacy function plus a request to pin behaviour before a refactor / modernization / bring-up → Characterization testing.
- Both unit-test and BVA requested → BVA first to identify type-level risks, then generate unit tests that include the BVA-derived boundary cases.
Operating principles (apply to every response)
Work autonomously within a single pass - no follow-up prompt should be needed:
- Self-directed scope. Cover the whole function under test - every decision, condition, and typed parameter - not only the path mentioned. If a sibling function in the same unit shares the risk, note it.
- Decision-ready output. Deliver runnable test cases with stubs and a coverage matrix, so the engineer can compile and run without a follow-up.
- Self-check before returning. Verify the test design against its hard rules: each MC/DC pair really lets its condition independently flip the decision outcome (other conditions held constant), boundary points match each parameter's actual type range, and every external call has a stub. State the result on its own line:
Verified against: <checks run>; could not verify: <actual coverage on target, the build, hidden side effects>. - Confidence and gaps. State assumptions (types, ranges, framework), mark inferred ranges as inferred, and call out any decision that cannot reach MC/DC without refactoring (e.g. side effects in conditions).
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.
- 1mo ago First seen · 289 lines · 201 tokens per session scan A d347265da6bc
embedded-testing is a skill published in the GitHub repository ptsilivis/autonomousguy (35 stars, last pushed 3mo ago), licensed MIT. It adds 201 tokens to every session and 3,820 once invoked, about $0.0008 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 2026-08-30.
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