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/linuxfoundation/lfx-self-serve/self-serve-devnpx skills add linuxfoundation/lfx-self-serve --skill self-serve-devgit clone --depth 1 https://github.com/linuxfoundation/lfx-self-serveWhat 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 | $0.00065 | $0.02916 |
| Opus 5 | $0.00032 | $0.01458 |
| Sonnet 5 | $0.00013 | $0.00583 |
| Haiku 4.5 | $0.00006 | $0.00292 |
Grade A, and why
self-serve-dev 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 3d 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 — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LFX One Development Guide
You are helping a contributor build within the LFX One codebase. This skill handles all development work: creating new features, fixing bugs, modifying existing code, refactoring, and full end-to-end feature builds.
Important: You are integrating features within existing architecture — not making architectural decisions. If the work requires changes to routing, auth, middleware, or infrastructure, flag it for a code owner.
Pre-edit hygiene
Before every meaningful edit:
- Re-read the file with
view— do not trust prior conversation history. Files change; context drifts. - Run
yarn check-typesafter multi-file changes to catch type drift early. - Stop and ask if the request conflicts with conventions in
CLAUDE.mdor.claude/rules/.
Default to small, atomic changes. If a request spans more than one module or touches both client and SSR server, surface that and ask whether to split.
Step 1: Start from Latest Main & Track Work
Follow the "Starting New Work" rule in development-rules.md — checkout main, pull latest, and create a feature branch before writing any code.
Tracking Ticket (JIRA or GitHub Issue)
Before writing code, ensure the work is tracked:
- Check for an existing ticket — a JIRA ticket in the
LFXV2project, or a GitHub Issue onlinuxfoundation/lfx-self-serve(e.g. under an epic on the Kanban board) - Create one if needed — JIRA ticket (assign to the current user and current sprint) or a GitHub Issue via
gh issue create; don't create both for the same work - Branch name must include the ticket:
feat/LFXV2-<number>,fix/LFXV2-<number>for JIRA, orfeat/issue-<number>,fix/issue-<number>for a GitHub Issue - Reference
.claude/rules/commit-workflow.mdfor naming conventions
Step 2: Plan the Feature (Ideation)
Ask the contributor what they're building. Before writing any code, create a plan that answers:
What ships with it
4 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.
- 3d ago First seen · 258 lines · 65 tokens per session scan A 345f18965673
self-serve-dev is a skill published in the GitHub repository linuxfoundation/lfx-self-serve (11 stars, last pushed 3d ago), licensed MIT. It adds 65 tokens to every session and 2,916 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
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auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…