ai-development-guide

ai-development-guide is a skill for Codex from shinpr/codex-workflows. It costs 40 tokens per session (1,255 once invoked), scanned A, original, MIT.

A software development guide focused on finding the real cause of bugs and keeping changes within the required scope. It also covers checking that fixes and quality improvements are complete.

In plain words
What is it for?
Use it when fixing bugs, reviewing code quality, refactoring, making technical decisions, or checking implementation quality.
Why use it?
It helps avoid superficial fixes, unnecessary refactoring, and changes that are not supported by evidence. It keeps attention on the affected behavior and its governing requirements.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it when fixing bugs, reviewing code quality, refactoring, making technical decisions, or checking implementation quality.

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Install with agentmods
npx agentmods add skills/shinpr/codex-workflows/ai-development-guide
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 shinpr/codex-workflows --skill ai-development-guide
Clone the repo
git clone --depth 1 https://github.com/shinpr/codex-workflows

Made for: Codex.

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-development-guide

README.md
[![agentmods](https://agentmods.dev/badge/skills/shinpr/codex-workflows/ai-development-guide/github.svg)](https://agentmods.dev/skills/shinpr/codex-workflows/ai-development-guide)
Your own site
<a href="https://agentmods.dev/skills/shinpr/codex-workflows/ai-development-guide"><img src="https://agentmods.dev/badge/skills/shinpr/codex-workflows/ai-development-guide/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-development-guide

Your own site · 80×15
<a href="https://agentmods.dev/skills/shinpr/codex-workflows/ai-development-guide"><img src="https://agentmods.dev/badge/skills/shinpr/codex-workflows/ai-development-guide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,255 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 $0.00040 $0.01255
Opus 5.5 $0.00016 $0.00502
Sonnet 5.5 $0.00008 $0.00251
Haiku 4.5 $0.00004 $0.00126

Measured 7d ago against content hash 40ce5bdaa5ef, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-development-guide 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 7d 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.

.agents/skills/ai-development-guide/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Development Guide

Reference

Read references/frontend.md only for React or TypeScript frontend work whose changed behavior or quality failure needs those rules.

Outcome Boundary

Ground the required outcome in the governing task or design sources and the user's explicit instructions. Choose work by what the consumer must be able to do or judge, preserving that result while reducing the means needed to deliver it.

When an unverified premise could invalidate the approach, check it by the cheapest sufficient means before expanding dependent work. When results contradict that premise, reconsider the approach before patching its parts. Keep this reasoning in the current task; a small request needs no additional artifact.

Phase passage permits progress; technical necessity remains a separate evidence-backed lifecycle decision. Reconsider and remove or supersede means recorded in a Design Doc, ADR, plan, AC, or test when the required outcome remains satisfied. Preserve user-required outcomes, explicit constraints, actual consumer contracts, and external-action authority. For authorized feature removal, check remaining consumers; the removed entry point and its now-unused backend create no preservation obligation. Coordinate affected source and consumer updates through the orchestrator; existing execution authority continues for outcome-preserving technical reductions.

Investigate, repair, refactor, and verify only as far as one of these requires:

  • a user-required outcome or explicit constraint;
  • a dependency needed for that outcome;
  • an observed failure or contradiction in the changed path;
  • an evidence-backed material risk created or exposed by the change.

Evidence makes a candidate evaluable. Adopt work only when it is necessary now and its benefit justifies total lifecycle cost over no change, subtraction, or reuse. A required outcome defect still needs a sufficient response. Keep unrelated debt outside the change.

Root-Cause Discipline

Read the full file on GitHub · 86 lines

Files

What ships with it

2 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. 7d ago Changed · +2 lines 40ce5bdaa5ef
  2. 1mo ago Changed · +4 lines db0e19d3225f
  3. 1mo ago First seen · 80 lines · 40 tokens per session scan A 1b530138fd4a

Subscribe to this mod's changes

ai-development-guide is a skill published in the GitHub repository shinpr/codex-workflows (39 stars, last pushed 2d ago), licensed MIT. It adds 40 tokens to every session and 1,255 once invoked, about $0.0002 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 2026-08-30.

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