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 skills add marchatton/agent-skills --skill breadboardinggit clone --depth 1 https://github.com/marchatton/agent-skillsWrote 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/marchatton/agent-skills/breadboarding)<a href="https://agentmods.dev/skills/marchatton/agent-skills/breadboarding"><img src="https://agentmods.dev/badge/skills/marchatton/agent-skills/breadboarding/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/marchatton/agent-skills/breadboarding"><img src="https://agentmods.dev/badge/skills/marchatton/agent-skills/breadboarding.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 | $0.00074 | $0.01978 |
| Opus 5.5 | $0.00030 | $0.00791 |
| Sonnet 5.5 | $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 1mo 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.
- 1mo 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 7mo ago), licensed MIT. It adds 74 tokens to every session and 1,978 once invoked, about $0.0003 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 2026-08-31.
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