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 agentmods add skills/lablup/backend.ai/code-tracenpx skills add lablup/backend.ai --skill code-tracegit clone --depth 1 https://github.com/lablup/backend.aiWhat 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 | $0.00051 | $0.00690 |
| Opus 5 | $0.00026 | $0.00345 |
| Sonnet 5 | $0.00010 | $0.00138 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
code-trace 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 yesterday.
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.
The source is not reproduced here
Licensed LGPL-3.0
The repository is licensed LGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- yesterday First seen · 54 lines · 51 tokens per session scan A 93feda19bfb4
code-trace is a skill published in the GitHub repository lablup/backend.ai (672 stars, last pushed 3d ago), licensed LGPL-3.0. It adds 51 tokens to every session and 690 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.
Other skills, from other repositories
fastapi-docs
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api-design-framework
Use this skill when designing REST, GraphQL, or gRPC APIs. Provides comprehensive API design patterns, versioning strategies, error handling conventions, authentication approaches, and OpenAPI/AsyncAPI templates. Ensures consistent, well-documented, and developer-friendly APIs across all backend services.
alembic-migration
Create, review, and apply database schema changes with Alembic. Use whenever a SQLAlchemy model is added or changed, a column/index/constraint needs to change, or a data backfill is required — anything that alters the PostgreSQL schema.
wiki_submit
Submit wiki documentation pages to Wegent backend API. Simplifies the HTTP POST process for wiki content submission.
create-tutorial
Scaffold a new Membrane API Gateway tutorial in the api-gateway repo — the numbered self-teaching YAML under distribution/tutorials/ /, its support files and README links, and the matching auto-discovered integration test. Use whenever the user asks to create, add, write, or scaffold a tutorial (or a tutorial step)…
review-branch
Review the current git branch against master — code quality, refactoring opportunities, regressions, correctness, and test coverage — and print a severity-grouped markdown report. Use whenever the user asks to review the branch, review their changes against master, do a pre-PR / pre-merge review, or asks "is this…