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.
git clone --depth 1 https://github.com/olehsvyrydov/AI-development-teamWrote 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/commands/olehsvyrydov/ai-development-team/design-sprint)<a href="https://agentmods.dev/commands/olehsvyrydov/ai-development-team/design-sprint"><img src="https://agentmods.dev/badge/commands/olehsvyrydov/ai-development-team/design-sprint/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/commands/olehsvyrydov/ai-development-team/design-sprint"><img src="https://agentmods.dev/badge/commands/olehsvyrydov/ai-development-team/design-sprint.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 | $0.00026 | $0.00573 |
| Opus 5 | $0.00013 | $0.00287 |
| Sonnet 5 | $0.00005 | $0.00115 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
design-sprint 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 9d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Sprint Workflow
This command orchestrates the complete design-to-implementation workflow.
Workflow Overview
+------------------+ +------------------+ +-------------------+
| 1. Discovery |---->| 2. Design Spec |---->| 3. Implementation |
| (/ui) | | (/ui) | | (/fe) |
+------------------+ +------------------+ +-------------------+
| | |
v v v
Questions to Save spec to Read spec from
clarify scope ui-design/ ui-design/
Usage
/design-sprint {feature-name}
/design-sprint sprint-5 user-profile
Steps to Execute
Step 1: Discovery Phase (/ui)
First, invoke the UI Designer to understand requirements:
/ui Design the {feature-name} feature.
Start with discovery questions before creating any designs.
Wait for /ui to:
- Ask discovery questions
- Get user answers
- Create design blueprint
Step 2: Design Specification (/ui)
After discovery, /ui will create the design spec:
Save the design specification to:
docs/ui-design/{sprint}/{feature-name}.md
Use the DESIGN_SPEC_TEMPLATE.md format.
Include:
- Visual design (colors, typography, spacing)
- Component structure
- Responsive breakpoints
- Accessibility requirements
- Ready-to-implement React/Tailwind code
Step 3: Implementation (/fe)
Once design is saved, invoke frontend developer:
/fe Implement the {feature-name} feature.
Check the design spec at docs/ui-design/{sprint}/{feature-name}.md
/fe will:
- Auto-read the design spec
- Implement exactly as designed
- Write tests
- Verify visually
Step 4: Verification
After implementation:
- /ui verifies implementation against design spec (design QA)
- Run accessibility checks
- Execute visual regression tests
- /rev reviews code quality
Example Flow
User: /design-sprint sprint-6 job-search-filters
1. Claude invokes /ui for discovery
2. /ui asks: "What filter types? Date range? Location radius?"
3. User provides answers
4. /ui creates design spec -> saves to docs/ui-design/sprint-6/job-search-filters.md
5. Claude invokes /fe
6. /fe reads spec, implements feature
7. Tests written and passing
8. /ui verifies implementation
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.
- 9d ago First seen · 99 lines · 26 tokens per session scan A 561e476844b3
design-sprint is a command published in the GitHub repository olehsvyrydov/AI-development-team (16 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 573 once invoked, about $0.0001 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 commands, from other repositories
research-verify
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color-palette
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theme
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ux-extract
Exhaustively extract UX patterns from a reference web app into a reusable pattern library.
p3-ux-wireframes
Creates wireframes (ASCII art) for the most important screens with interaction descriptions.
p6-a11y
Systematically checks the application for accessibility. Each A11y dimension is a separate sub-command.