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ai-native-sdlc

ai-native-sdlc is a skill for Claude Code from timwukp/agent-skills-best-practice. It costs 172 tokens per session (3,149 once invoked), scanned A, original, MIT.

A workflow for taking a software change from an idea to deployment through documented stages such as intent, design, implementation, testing, review, and release.

In plain words
What is it for?
It helps manage change artifacts, enforce stage transitions with hooks and CI, define verification targets, record review findings, and gate releases.
Why use it?
It creates a machine-readable audit trail and uses automated gates so work proceeds in the intended order.

Skill for Claude Code

Written for Claude Code: PreToolUse hook event.

Part of the engineering-skills plugin — 18 skills shipped together

not rated 10repo changed 2d ago A scan SkillSpector: pass 172 tokens original MIT

Good fit It helps manage change artifacts, enforce stage transitions with hooks and CI, define verification targets, record review findings, and gate releases.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/timwukp/agent-skills-best-practice/ai-native-sdlc
View source ↗ timwukp/agent-skills-best-practice
Install

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.

Any agent
npx skills add timwukp/agent-skills-best-practice --skill ai-native-sdlc
Clone the repo
git clone --depth 1 https://github.com/timwukp/agent-skills-best-practice

Made for: Claude Code.

Or install engineering-skills, the plugin that ships this one along with the rest of its 18 skills.

Wrote 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.

agentmods badge for ai-native-sdlc

README.md
[![agentmods](https://agentmods.dev/badge/skills/timwukp/agent-skills-best-practice/ai-native-sdlc/github.svg)](https://agentmods.dev/skills/timwukp/agent-skills-best-practice/ai-native-sdlc)
Your own site
<a href="https://agentmods.dev/skills/timwukp/agent-skills-best-practice/ai-native-sdlc"><img src="https://agentmods.dev/badge/skills/timwukp/agent-skills-best-practice/ai-native-sdlc/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.

agentmods 80×15 button for ai-native-sdlc

Your own site · 80×15
<a href="https://agentmods.dev/skills/timwukp/agent-skills-best-practice/ai-native-sdlc"><img src="https://agentmods.dev/badge/skills/timwukp/agent-skills-best-practice/ai-native-sdlc.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 172 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,149 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00172 $0.03149
Opus 5 $0.00086 $0.01574
Sonnet 5 $0.00034 $0.00630
Haiku 4.5 $0.00017 $0.00315

Measured 2d ago against content hash abe69e88434e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ai-native-sdlc 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 2d ago.

The scan reads SKILL.md. This mod also ships 22 executable files (scripts/build_review_prompt.py, scripts/make_sbom.py, scripts/mutation_proof.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/skills/ai-native-sdlc/SKILL.md · 226 lines

How it starts

The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI-Native SDLC

Take a change from idea to production as a loop around the agent, not a linear human relay. Each stage ends by committing one machine-readable artifact, and the next stage begins by reading it. The chain of commits becomes the audit trail: who asked for what, what the agent produced, and who approved it.

Plan     ->  intent.md
Design   ->  spec.md
Build    ->  plan.md  ->  diff + tests
Test     ->  a verification target + evals/
Deploy   ->  PR + REVIEW.md findings  ->  gated release
Maintain ->  bands.yaml breach  ->  writes a new intent.md   (loop closes)

Instructions

  1. Identify the stage. Read .sdlc/active for the current slug; artifacts live in intent/<slug>/. If there is no active slug, the work starts at Stage 1.
  2. Read the input artifact before producing the output artifact. Never write spec.md without reading an accepted intent.md, and never edit source before plan.md is accepted.
  3. Run the gate rather than judging by eye: 
    python3 scripts/sdlc_gate.py intent/<slug> <design|build|test|deploy>
# exit 0 = gate open, exit 2 = gate closed (reason on stderr)
  4. Write the verification target BEFORE the implementation, run it, and confirm it FAILS. A test that has only ever been seen green is not evidence.
  5. Implement, then re-run it until green. If the implementation departs from plan.md, update plan.md in the same commit.
  6. Commit the artifact at the end of each stage. The commit is what advances the loop.
  7. Never approve your own work. Acceptance of intent.md / sign-off of spec.md is a human decision; do not flip a Status field on an artifact you authored.

Stage detail

Stage 1 — Plan → intent/<slug>/intent.md

Interview the originator until the idea is concrete: problem, desired outcome, affected users and systems, constraints, success criteria, open questions. Copy templates/intent.md. Gate: the product owner sets Status: accepted.

Read the full file on GitHub · 226 lines

Files

What ships with it

38 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.

Changes

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.

  1. 2d ago Changed · +31 lines abe69e88434e
  2. 5d ago Changed · +11 lines abd7077bb034
  3. 7d ago First seen · 184 lines · 172 tokens per session scan A 682444d2140a

Subscribe to this mod's changes

ai-native-sdlc is a skill published in the GitHub repository timwukp/agent-skills-best-practice (10 stars, last pushed 2d ago), licensed MIT. It adds 172 tokens to every session and 3,149 once invoked, about $0.0009 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 2026-09-03.

Building agentsClaude CodePlanningagent-skillsai-agentsawsbest-practicesclaude-skills
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