Borrowing it
Nothing to install: this file belongs to brianmontanaweb/agentic-design-system. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/brianmontanaweb/agentic-design-system/main/.claude/skills/add-component/SKILL.mdgit clone --depth 1 https://github.com/brianmontanaweb/agentic-design-systemWrote 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/brianmontanaweb/agentic-design-system/add-component)<a href="https://agentmods.dev/skills/brianmontanaweb/agentic-design-system/add-component"><img src="https://agentmods.dev/badge/skills/brianmontanaweb/agentic-design-system/add-component/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/brianmontanaweb/agentic-design-system/add-component"><img src="https://agentmods.dev/badge/skills/brianmontanaweb/agentic-design-system/add-component.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 | $0.00086 | $0.01580 |
| Opus 5.5 | $0.00034 | $0.00632 |
| Sonnet 5.5 | $0.00017 | $0.00316 |
| Haiku 4.5 | $0.00009 | $0.00158 |
Grade A, and why
add-component 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 2mo 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add Component (Orchestrator)
Scaffold a new component given $ARGUMENTS in the format <ComponentName> [core|agents].
This skill creates no files itself. It guards against overwrites, plans, gets approval once, then invokes five sub-skills in order via the Skill tool. Each sub-skill declares context: fork, so every invocation runs in a fresh subagent with no access to this conversation — a sub-skill cannot see the plan, the Figma data, or earlier file reads. Everything it needs must be passed explicitly in its args.
Gotchas
- Figma is optional — if the user skips the link, mark "Figma: skipped" in output and proceed immediately; never block on it.
- Approval happens once, here — after the Step 3 plan is approved, run all five sub-skills without asking again. The sub-skills do not have their own approval gates.
- Package inference default — when ambiguous, lean
agentsfor status/streaming/tool-related names; leancorefor anything that reads like a generic UI primitive (full rules in the shared conventions reference). - Agent-specific ARIA is decided in the plan, not retrofitted — pick the ARIA pattern in Step 3 from
shared/references/aria-patterns.mdand pass it toadd-component-source. - Theming is decided in the plan too — light/dark support comes from semantic tokens (see the Theming section of the shared conventions reference). Decide in Step 3 whether existing semantic tokens cover the component or new ones are needed; new tokens require both
_darkand_lightvalues. - Invoke sub-skills in the listed order — story, tests, and spec doc all read the source file; source must exist first. Verification runs last.
Step 0 — Check for existing component
Before doing anything else, check whether the component already exists in either package:
ls packages/core/src/<ComponentName>/<ComponentName>.tsx packages/agents/src/<ComponentName>/<ComponentName>.tsx 2>/dev/null
If any output is produced, the component already exists. Stop immediately and respond:
What ships with it
1 file 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.
- 2mo ago First seen · 123 lines · 86 tokens per session scan A af19dda1d895
add-component is a skill published in the GitHub repository brianmontanaweb/agentic-design-system (3 stars, last pushed 2mo ago), licensed MIT. It adds 86 tokens to every session and 1,580 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.
Other skills, from other repositories
critique
Adversarial design critique of the current work. Render it, look at it, and argue for rejection. Run after the gates are green, never instead of them.
design-qa
Set up or run design QA gates for token + hardcoded-value lint, automated a11y (axe), contrast, visual regression across variants/states/themes/RTL, and the manual a11y checklist. Use when the user wants CI quality gates, to prevent design regressions, or to QA a component/screen before shipping.
gate
Run the one-command quality gate and report the real N/N result. Use before claiming any build/review is done.
ship
Pre-release gate. Run the full gate, responsive + render checks, then produce the release checklist (README badge/current/changelog). Use before tagging a release.
kb-python-development
Reference data, not a reviewer. Python and wxPython development: packaging (PyInstaller/Nuitka), testing, desktop accessibility APIs, cross-platform paths, and framework patterns.
deepeval
Use when discussing or working with DeepEval (the python AI evaluation framework).