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.
git clone --depth 1 https://github.com/alinotfoundbtw/soundingWrote 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/commands/alinotfoundbtw/sounding/newrule)<a href="https://agentmods.dev/commands/alinotfoundbtw/sounding/newrule"><img src="https://agentmods.dev/badge/commands/alinotfoundbtw/sounding/newrule/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/commands/alinotfoundbtw/sounding/newrule"><img src="https://agentmods.dev/badge/commands/alinotfoundbtw/sounding/newrule.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 | $0.00016 | $0.00269 |
| Opus 5.5 | $0.00006 | $0.00108 |
| Sonnet 5.5 | $0.00003 | $0.00054 |
| Haiku 4.5 | $0.00002 | $0.00027 |
Grade A, and why
newrule 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.
What it actually says
Add a rule to $ARGUMENTS.
Follow the sequence, and do not skip step 2:
- Write the failing fixture first — the artifact that should trigger it.
- Write the fixture that must NOT trigger it. A plausible, well-written artifact that a careless pattern would catch. If you cannot think of one, the rule is probably too broad to add.
- Implement the rule in
src/sounding/rules/. It needs:- a
reference— the spec section or documented practice. Not optional. - a
fixstring, or aquestionwith options when intent is required - a severity: 15 / 7 / 3. When unsure, pick lower.
- a
- Two tests: fires on the bad case, silent on the good case.
- Run
/check. - Report the rule code, both fixtures, and what severity you chose and why.
Reminder: false positives are how a linter loses its audience. A rule that fires on careful work is worse than no rule.
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 · 24 lines · 0 tokens per session scan A 705edcb584eb
newrule is a command published in the GitHub repository alinotfoundbtw/sounding (4 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 269 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
compile
Compile a FIBER decision context (world + query) and report the oracle verdict, omission accounting, and certificate digest faithfully.
release-manager
Automated release coordination and deployment with ruv-swarm orchestration for seamless version management, testing, and deployment across multiple packages.
data-mesh-contract
Create federated data product contracts for mesh architectures with SLAs, governance, and interoperability guarantees (project).
atrs
Generate Algorithmic Transparency Recording Standard (ATRS) record for AI/algorithmic tools.
fr-rgpd
You are helping an enterprise architect generate a French CNIL Compliance Assessment — the French-specific GDPR layer applied by the CNIL (Commission Nationale de l'Informatique et des Libertés). Run this after /arckit-eu:eu-rgpd to add French obligations that go beyond the EU GDPR baseline.
flow-nexus-neural
Train and deploy neural networks in distributed sandboxes.