addyosmani/agent-skills is a collection of reusable workflows, quality checks, commands, and other instructions that guide AI coding agents through software development. It is for developers who want agents to follow consistent engineering practices, and the catalogue entries are its packaged skills, commands, agents, plugins, instructions, and hooks.
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/addyosmani/agent-skills/constraint-driven-developmentnpx skills add addyosmani/agent-skills --skill constraint-driven-developmentgit clone --depth 1 https://github.com/addyosmani/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/addyosmani/agent-skills/constraint-driven-development)<a href="https://agentmods.dev/skills/addyosmani/agent-skills/constraint-driven-development"><img src="https://agentmods.dev/badge/skills/addyosmani/agent-skills/constraint-driven-development.svg" alt="Measured on agentmods" 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 | $0.00154 | $0.04948 |
| Opus 5 | $0.00077 | $0.02474 |
| Sonnet 5 | $0.00031 | $0.00990 |
| Haiku 4.5 | $0.00015 | $0.00495 |
Grade A, and why
constraint-driven-development 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- constraint-driven-development — 98% identical, 1 lines differ
How it starts
The opening of the file, as written. The whole thing — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Constraint-Driven Development
Overview
Other skills in this pack describe what good looks like. code-review-and-quality gives you five axes. test-driven-development gives you a cycle. security-and-hardening gives you a threat list. All of that lives in prose the agent reads and may or may not follow, and none of it survives the end of the session.
This skill produces something different: a written record of this project's bar, with numbers, that outlives the conversation and can be checked mechanically.
The reason matters. When you wrote the code, reading it told you whether it was any good. An agent writes more in an afternoon than you will read that week, so the judgement moves out of your head and into checks that run around the loop. Those checks need to exist, they need numbers you actually chose, and they need to fire close enough to the work that the agent fixes its own output.
Spec-driven development says what to build. Test-driven development proves it works. Constraint-driven development defines what "good enough to ship" means, before anyone argues about it in a pull request.
When to Use
Apply this skill when:
- Starting a project or a significant feature and no quality bar is written down
- The user asks to "set up constraints", "add quality gates", "define our standards", or "stop the agent shipping junk"
- An agent is producing volume nobody is reading line by line
- CI has checks but nobody can say which ones block a merge and which ones are decoration
- Coverage, performance, or accessibility numbers get argued about per-PR instead of decided once
- You're about to run
/build autoor any autonomous loop, and the only thing standing between it and main is a test suite the agent also wrote
When NOT to use:
- The project already has a
CONSTRAINTS.mdand the user isn't changing it — read it and follow it instead - One-off scripts, spikes, throwaway prototypes
- The user wants a code review right now (
code-review-and-quality) or a CI pipeline built (ci-cd-and-automation) - Pre-product-market-fit code with a two-week expected lifetime — the floor below is still worth it, the rest isn't
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.
- 6d ago First seen · 312 lines · 154 tokens per session scan A 19d0aba70ced
constraint-driven-development is a skill published in the GitHub repository addyosmani/agent-skills (92,476 stars, last pushed today), licensed MIT. It adds 154 tokens to every session and 4,948 once invoked, about $0.0008 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 skills, from other repositories
test-driven-development
Drives development with tests via Red-Green-Refactor and the Prove-It pattern, with hard rules against weakening assertions or faking green suites. Use when implementing any logic, fixing any bug, or changing any behavior. Triggers on "add a feature", "fix this bug", "write tests", or any task where done must be…
ai-output-validation
Validates, parses, and sanitizes AI-generated outputs before they reach end users or downstream systems. Structured output enforcement, schema validation, and fallback handling.
debugging-and-error-recovery
Guides systematic root-cause debugging with hard rules against guess-fixes and symptom suppression. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Triggers on "this is broken", "tests are failing", "why doesn't this work", or any error output.
error-handling
Graceful degradation and meaningful error messages. Errors are first-class citizens, not afterthoughts. Every error path is designed, not discovered.
goal-driven-execution
Transforms imperative instructions into declarative goals with verifiable success criteria. Enables autonomous looping until verified completion.
think-before-coding
Forces explicit reasoning before writing any code. Surfaces assumptions, manages confusion, and prevents hallucination by demanding clarity upfront.