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 grcengineering/companion --skill cross-domain-translatorgit clone --depth 1 https://github.com/grcengineering/companionWrote 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/grcengineering/companion/cross-domain-translator)<a href="https://agentmods.dev/skills/grcengineering/companion/cross-domain-translator"><img src="https://agentmods.dev/badge/skills/grcengineering/companion/cross-domain-translator.svg" alt="Measured on agentmods" 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 | $0.00066 | $0.00471 |
| Opus 5 | $0.00033 | $0.00235 |
| Sonnet 5 | $0.00013 | $0.00094 |
| Haiku 4.5 | $0.00007 | $0.00047 |
Grade A, and why
cross-domain-translator 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.
What it actually says
cross-domain-translator
What
Use patterns from adjacent disciplines to make GRC concepts easier to understand and apply.
When
- The learner is stuck.
- A concept is too abstract.
- A metaphor would expose the structure of the problem.
- The learner needs to transfer a pattern from one context to another.
Not For
- Plain first-pass explanation. Use
concept-tutor. - Full scenario practice. Use
practice-scenario. - Producing operational advice through a metaphor.
Inputs
- GRC concept or stuck point.
brain/cross-domain-transfer.md.- Optional corpus source when the translated idea needs grounding.
Steps
- Name the GRC concept or stuck point.
- Pick one adjacent-domain pattern from
brain/cross-domain-transfer.md. - Explain the native pattern briefly.
- Translate it into GRC.
- Name where the metaphor breaks.
- Ask the learner to apply the new lens to a fictional or abstracted situation.
Validation
- The metaphor clarifies structure rather than decorating the answer.
- The learner can state where the analogy breaks.
- The final transfer stays learning-safe.
Gotchas
- Do not force a metaphor when direct explanation is clearer.
- Always name the break point; metaphors become misleading when treated as exact.
- If the learner uses the metaphor to request live advice, restate the boundary.
Failure Modes
- Cute but useless: replace the metaphor with a direct distinction.
- Overextended analogy: stop at the useful structural match.
- Operational drift: translate reasoning patterns, not real decisions.
Examples
- User says controls feel abstract -> Translate control design through product feedback loops, then name where the analogy breaks.
- User understands CI/CD but not evidence pipelines -> Map build artefacts to evidence generation using a toy workflow.
- User asks for a metaphor to decide a real vendor -> Refuse the decision and use a fictional pattern transfer instead.
What ships with it
3 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.
- 8d ago First seen · 63 lines · 66 tokens per session scan A 57e558aa078b
cross-domain-translator is a skill published in the GitHub repository grcengineering/companion (33 stars, last pushed 3mo ago), licensed MIT. It adds 66 tokens to every session and 471 once invoked, about $0.0003 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 2026-08-30.
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