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/marchatton/agent-skills/breadboardingnpx skills add marchatton/agent-skills --skill breadboardinggit clone --depth 1 https://github.com/marchatton/agent-skillsWhat 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 | $0.00074 | $0.01978 |
| Opus 5 | $0.00037 | $0.00989 |
| Sonnet 5 | $0.00015 | $0.00396 |
| Haiku 4.5 | $0.00007 | $0.00198 |
Grade A, and why
breadboarding 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 — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Breadboarding
Purpose
Produce a Shape Up style breadboard that is concrete enough to guide a build, without collapsing into pixel-perfect UI spec or a full-code hairball.
Based on Shape Up and Ryan Singer's work.
Treat affordances as the simplifying primitive.
- UI affordances: things a user can do (type, click, scroll) or see (states/messages) that matter to the flow.
- Code affordances: things the system can do (call a function, observe an observable, write/read state, navigate) that cause the UI affordances to change.
Use those to build a lightweight model of the current system and the proposed change.
When to use
- Reach the “rough out the elements” stage and need to turn an idea into buildable parts.
- Shape a change to a pre-existing system and need to understand what the system actually does today.
- Compare a new concept against an existing feature and decide whether to duplicate vs extract shared logic.
- Pick up a shaping effort after a gap and need a fast re-orientation: current state, chosen approach, and what’s still unsolved.
Inputs to request or infer
Prefer working with whatever exists. If inputs are missing, use ask-questions-if-underspecified skill
- Appetite / timebox and any hard boundaries.
- Problem statement and success definition.
- Brief (problem, goals, in/out scope). If missing, pause and draft a brief first.
- Requirements list (or a rough list of must-haves).
- Entry point(s): where the user starts, how they discover the feature.
- Existing system context: routes/screens, key components, services, data stores.
- Any comparable feature(s) to analyse for reuse.
Workflow
1) Establish the “right level of abstraction”
- Avoid full wireframes and visual design.
- Prefer words and connections over pictures.
- Focus on “what’s connected to what” (topology) and “what changes state”.
Use the breadboard primitives:
- Places: screens/pages/modals/menus that can be navigated to.
- Affordances: actions and information at a place (buttons, fields, copy, empty/loading states).
- Connection lines: how an affordance moves between places or triggers work.
What ships with it
9 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.
- references/examples/letter-search-example.md 4.5 KB
- references/shapeup-breadboarding-notes.md 1.5 KB
- references/templates/breadboard-pack-template.md 1.8 KB
- references/templates/brief-template.md 1.6 KB
- references/templates/extract-vs-duplicate-template.md 1.6 KB
- references/templates/fit-check-template.md 524 B
- references/templates/parts-bom-template.md 445 B
- references/templates/wiring-diagram-mermaid-template.md 1.5 KB
- scripts/render_mermaid_from_edges.py 3.7 KB runs code
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 · 218 lines · 74 tokens per session scan A cb8dd97c49e5
breadboarding is a skill published in the GitHub repository marchatton/agent-skills (5 stars, last pushed 5mo ago), licensed MIT. It adds 74 tokens to every session and 1,978 once invoked, about $0.0004 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 2026-08-31.
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…