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/sukoji/loadout/recommendnpx skills add sukoji/loadout --skill recommendgit clone --depth 1 https://github.com/sukoji/loadoutWhat 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 | $0.02516 |
| Opus 5 | $0.00026 | $0.01258 |
| Sonnet 5 | $0.00010 | $0.00503 |
| Haiku 4.5 | $0.00005 | $0.00252 |
Grade B, and why
recommend scanned grade B with 1 finding 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 2d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
merge into `./.codex/config.toml` under `[mcp_servers.<id>]`: use `command`/`args`/`env` for stdio and How it starts
The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loadout — recommend and apply
Your job: look at THIS project, figure out what it is, and hand the user a short, ranked loadout of agent extensions worth adding — then apply exactly the ones they choose. You are a recommender and installer, not a list-dumper. Never paste the whole catalog.
Step 0 — Load the catalog (3 tiers)
Resolve the plugin root first from the directory two levels above this SKILL.md. A host-provided
PLUGIN_ROOT or CLAUDE_PLUGIN_ROOT may be used when available, but the workflow must not depend on
either variable. Refer to the resolved directory as <plugin-root> below.
Read the curated (Tier 1) files fully — they're small and hand-verified:
<plugin-root>/catalog/mcp.json<plugin-root>/catalog/skills.json<plugin-root>/catalog/hooks.json<plugin-root>/catalog/domains.json<plugin-root>/catalog/community.json(Tier 3, small)
Each item has id, name, description, domains, signals. MCP items carry a config, hook/setting
items a settings object, skill items an install block.
Tier 2 (official marketplace) is large (catalog/ecosystem.json, ~280 entries) — do NOT read it whole.
After you know the project's signals (Step 1), Grep ecosystem.json for those signal tokens to pull only
the handful of official plugins that match. Each is a tier: "official", verified Anthropic-marketplace
plugin installed with the /plugin install <name>@claude-plugins-official command in its install.commands.
Tier meaning: curated = auto-apply safe; official = trusted, install via /plugin; community
(Tier 3) = UNVERIFIED — only surface if the user asks to "discover"/see more, label it clearly, and never
auto-apply it. Items with "optIn": "token-saver" are never in discover or the domain loadout — offer
them only in the separate token-saver step (Step 3).
Step 1 — Profile the project
Detect what the repo is. Be fast and evidence-based — do not ask the user things you can read:
- Languages / frameworks / package managers: look for
package.json(and its deps — react, next, vue, svelte, express, nestjs, prisma…),requirements.txt,pyproject.toml,go.mod,Cargo.toml,pom.xml,Gemfile,pubspec.yaml,*.xcodeproj,build.gradle. - Infra / CI:
Dockerfile,docker-compose*,.github/workflows,*.tf,k8s/helm. - Data/ML:
*.ipynb,numpy/pandas/torch/tensorflowin deps,wandb/mlflow. - Research / academic:
*.tex,*.bib,papers/dir,arxivin deps. - Security surface: auth/payment/crypto libs, presence of
.env. - What's already set up: read existing
.mcp.json,.claude/settings.json,.claude/settings.local.json,.codex/config.toml,.codex/hooks.json,CLAUDE.md, andAGENTS.md. Never recommend something already installed.
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.
- 2d ago First seen · 153 lines · 51 tokens per session scan B f7e7c20b1c14
recommend is a skill published in the GitHub repository sukoji/loadout (2 stars, last pushed 2d ago), licensed MIT. It adds 51 tokens to every session and 2,516 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
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…