Borrowing it
Nothing to install: this file belongs to guzus/ai-research-arm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/guzus/ai-research-arm/main/.agents/skills/gen-research-ko-backfill/SKILL.mdgit clone --depth 1 https://github.com/guzus/ai-research-armWrote 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/guzus/ai-research-arm/gen-research-ko-backfill)<a href="https://agentmods.dev/skills/guzus/ai-research-arm/gen-research-ko-backfill"><img src="https://agentmods.dev/badge/skills/guzus/ai-research-arm/gen-research-ko-backfill/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/guzus/ai-research-arm/gen-research-ko-backfill"><img src="https://agentmods.dev/badge/skills/guzus/ai-research-arm/gen-research-ko-backfill.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 | $0.00023 | $0.00694 |
| Opus 5.5 | $0.00009 | $0.00278 |
| Sonnet 5.5 | $0.00005 | $0.00139 |
| Haiku 4.5 | $0.00002 | $0.00069 |
Grade A, and why
gen-research-ko-backfill 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 21d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gen Research Ko Backfill
Publish a Korean translation of an existing ARA generative-research article by dispatching the repo's translate-generative-research.yml ("Korean Generative Research Backfill"). That workflow is the publication path: it resolves the canonical source, translates in an isolated adapter, checks source/translation parity, writes through the canonical writer, verifies the exact commit, and lands it as a review PR (or auto-merges on request). main is PR-only, so do not translate and commit locally instead. The dashboard is static and manifest-driven: do not add runtime translation.
First-Principles Check
Before dispatching, answer:
- Which article is the target, and does
research/generative/index.jsonon the default branch contain its slug? - Is there already a Korean artifact under
translations.ko? If yes, did the user ask to replace it? - Does the user want the review PR (the default) or an auto-merge?
If the target slug does not exist, stop and ask for the correct article.
Workflow
- Resolve the repo and the target article from an up-to-date default branch.
cd "$(git rev-parse --show-toplevel)"
git fetch origin
git show origin/main:research/generative/index.json \
| jq -r '.[] | select(.slug=="<slug>") | [.slug, .file, (.translations.ko.file // "")] | @tsv'
- Dispatch the backfill.
gh workflow run translate-generative-research.yml -f slug="<slug>"
Add -f overwrite=true only when a Korean version exists and the user asked to replace it. Add -f auto_merge=true only when the user asked to skip the review PR.
- Follow the run to completion.
gh run list --workflow translate-generative-research.yml --limit 3
gh run watch <run-id> --exit-status
A failed run is a failed backfill: report the failing step and its log excerpt (gh run view <run-id> --log-failed), and do not retry by publishing another way. The run summary names the artifact path and, in review mode, the PR (branch prefix automation/ko-backfill).
What ships with it
1 file 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.
- 21d ago First seen · 63 lines · 23 tokens per session scan A 40d3cd170d59
gen-research-ko-backfill is a skill published in the GitHub repository guzus/ai-research-arm (14 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 694 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 2026-10-16.
gen-research-ko-backfill compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| gen-research-ko-backfillguzus/ai-research-arm | Skill | 14 | today | MIT | A | 23 | Codex |
| language-translatorclowlove/Hermes-House | Skill | 14 | yesterday | none | A | 52 | Claude Code, Codex |
| marketing-cross-border-ecommerceclowlove/Hermes-House | Skill | 14 | yesterday | none | A | 71 | Claude Code, Codex |
| marketing-china-market-localization-strategistclowlove/Hermes-House | Skill | 14 | yesterday | none | A | 48 | Claude Code, Codex |
| ai-translatorclowlove/Hermes-House | Skill | 14 | yesterday | none | A | 24 | Claude Code, Codex |
| pr-review-triagecobusgreyling/loop-engineering | Skill | 12k | yesterday | MIT | A | 35 | Claude Code |
| intl-expansionalirezarezvani/claude-skills | Skill | 29k | yesterday | MIT | A | 27 | Claude Code |