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 babyworm/rtl-agent-team --skill rtl-conformance-testgit clone --depth 1 https://github.com/babyworm/rtl-agent-teamWrote 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/babyworm/rtl-agent-team/rtl-conformance-test)<a href="https://agentmods.dev/skills/babyworm/rtl-agent-team/rtl-conformance-test"><img src="https://agentmods.dev/badge/skills/babyworm/rtl-agent-team/rtl-conformance-test/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/babyworm/rtl-agent-team/rtl-conformance-test"><img src="https://agentmods.dev/badge/skills/babyworm/rtl-agent-team/rtl-conformance-test.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00041 | $0.01792 |
| Opus 5 | $0.00020 | $0.00896 |
| Sonnet 5 | $0.00008 | $0.00358 |
| Haiku 4.5 | $0.00004 | $0.00179 |
Grade A, and why
rtl-conformance-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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Use_When>
- RTL passes functional verification and standards compliance must be confirmed.
- Codec standard version has changed and re-conformance is required.
- A specific ITU-T JVT conformance suite must be run against the RTL. </Use_When>
<Do_Not_Use_When>
conformance_report.jsonfromref-modeldoes not exist — runref-modelfirst.- Non-codec RTL design — this skill is specific to video codec standards compliance. </Do_Not_Use_When>
<Why_This_Exists> Standards compliance cannot be inferred from internal functional verification. JM/HM produce the normative reference bitstreams, and bitexact match is the only accepted evidence of conformance for codec IP submitted to standards bodies or licensees. </Why_This_Exists>
Prerequisites
conformance_report.json(fromref-model) present — ref model gate must pass first.- JM 19.0 (H.264) or HM 16.20 (H.265) installed and on
PATH. - RTL passes
rtl-p5s-func-verify(functional verification complete). - Conformance test vectors present at
sim/conformance/vectors/.
If missing: WARNING — halt and instruct user to resolve the missing prerequisite before proceeding.
<Responsibility_Boundary>
- Scripts (
conformance_compare.py) handle deterministic byte-level bitstream comparison. - LLM handles test vector selection, simulation orchestration, failure diagnosis, and spec-section attribution.
- Contract surface: 100% bitexact match required; any divergence is a hard FAIL with byte offset + hex values recorded. </Responsibility_Boundary>
Apply steps 1-7 to every requested vector suite — do not stop after the first.
<Tool_Usage>
Task(subagent_type="rtl-agent-team:vcodec-syntax-entropy-expert",
prompt="Select H.264 conformance test vectors applicable to CABAC encoder. "
"List vector files and JM version to use.")
Task(subagent_type="rtl-agent-team:eda-runner",
prompt="Run RTL conformance simulation via Bash CLI for each vector in "
"sim/conformance/vectors/. Compile and run: "
"scripts/run_sim.sh --sim iverilog --top tb_cabac_conformance "
"--outdir sim/conformance --trace rtl/cabac_encoder/cabac_encoder.sv "
"sim/top/tb_cabac_conformance.sv. "
"Compare output with JM 19.0: "
"cmp -l sim/conformance/rtl_output.bin sim/conformance/ref/jm_output.bin. "
"Report PASS/FAIL per vector with divergence byte offset.")
Task(subagent_type="rtl-agent-team:func-verifier",
prompt="Validate sim/conformance/results.json: verify all vectors ran, all have status, "
"every FAIL has divergence_byte and expected_hex/actual_hex fields.")
</Tool_Usage>
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 123 lines · 41 tokens per session scan A d4c2593a83eb
rtl-conformance-test is a skill published in the GitHub repository babyworm/rtl-agent-team (51 stars, last pushed 17d ago), licensed MIT. It adds 41 tokens to every session and 1,792 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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