incremental-implementation

incremental-implementation is a skill for Claude Code, Codex from vignesh2027/AI-AGENT-SKILLS. It costs 15 tokens per session (600 once invoked), scanned A, original, MIT.

A development method that builds software in small, working end-to-end pieces. A vertical slice means one small feature works through all relevant layers, such as the interface, API, service, database, and response.

In plain words
What is it for?
Use it for features taking more than a day, broad refactors, or work where you want to start with a minimal end-to-end version and expand it step by step.
Why use it?
It avoids waiting until a large implementation is finished before anything can be tested or used. Each increment provides a working result or useful feedback.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for features taking more than a day, broad refactors, or work where you want to start with a minimal end-to-end version and expand it step by step.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vignesh2027/ai-agent-skills/incremental-implementation
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 vignesh2027/AI-AGENT-SKILLS --skill incremental-implementation
Clone the repo
git clone --depth 1 https://github.com/vignesh2027/AI-AGENT-SKILLS

Made for: Claude Code, 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 incremental-implementation

README.md
[![agentmods](https://agentmods.dev/badge/skills/vignesh2027/ai-agent-skills/incremental-implementation/github.svg)](https://agentmods.dev/skills/vignesh2027/ai-agent-skills/incremental-implementation)
Your own site
<a href="https://agentmods.dev/skills/vignesh2027/ai-agent-skills/incremental-implementation"><img src="https://agentmods.dev/badge/skills/vignesh2027/ai-agent-skills/incremental-implementation/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 incremental-implementation

Your own site · 80×15
<a href="https://agentmods.dev/skills/vignesh2027/ai-agent-skills/incremental-implementation"><img src="https://agentmods.dev/badge/skills/vignesh2027/ai-agent-skills/incremental-implementation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 600 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.
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 $0.00015 $0.00600
Opus 5.5 $0.00006 $0.00240
Sonnet 5.5 $0.00003 $0.00120
Haiku 4.5 $0.00002 $0.00060

Measured 2mo ago against content hash 7d6ec69f08f2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

incremental-implementation 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.

skills/incremental-implementation/SKILL.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

Incremental implementation is the practice of delivering working software in the smallest useful increments. Each increment is deployable, testable, and provides value or learning. The goal is to eliminate the "everything works or nothing works" state that characterizes big-bang development.

When to Use

  • For any feature that will take more than 1 day to implement
  • When you feel the urge to implement "the whole thing" before shipping any of it
  • When designing a refactor that touches many files

Process

Step 1: Identify the minimum slice

Ask: what is the smallest version of this feature that proves the core hypothesis or delivers the core value? That is your first increment.

Step 2: Draw the vertical slice

A vertical slice cuts through all layers: UI → API → service → database → response. Implement all layers for the minimal slice before moving to the next feature.

Step 3: Build the walking skeleton

Implement the thinnest possible end-to-end version: returns hardcoded data, has no error handling, no edge cases. Make it work end-to-end first.

Step 4: Add tests for the skeleton

Write tests that cover the happy path of the walking skeleton. These tests will protect you as you add flesh to the skeleton.

Step 5: Flesh out the implementation

Add real data, error handling, and edge cases incrementally. Run tests after each addition.

Step 6: Keep each increment deployable

Every commit should leave the system in a deployable state. Use feature flags if necessary to hide incomplete work from end users.

Step 7: Review and ship each increment

Don't accumulate increments. Ship each one. Unreleased code is risk, not progress.

Anti-Rationalizations

"I need to build the whole thing before I can test it" This is the wrong architecture. If you can't test a slice without the whole system, redesign so you can.

"It's faster to build it all at once" It is faster to write code all at once. It is not faster to debug, review, and deploy code all at once.

Read the full file on GitHub · 66 lines

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. 2mo ago First seen · 66 lines · 15 tokens per session scan A 7d6ec69f08f2

Subscribe to this mod's changes

incremental-implementation is a skill published in the GitHub repository vignesh2027/AI-AGENT-SKILLS (2 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 600 once invoked, about $0.0001 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.

Related

incremental-implementation compared with skills from other repositories

incremental-implementation next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
incremental-implementationvignesh2027/AI-AGENT-SKILLSSkill22mo agoMITA15Claude Code, Codex
cw-gatesHmbown/CodewhaleSkill41k1mo agoMITA48Claude Code, Codex
feishuHmbown/CodeWhaleSkill41k6d agoMITA33Claude Code, Codex
eval-dataset-designbojieli/ai-agent-bookSkill57k1mo agoApache-2.0A138Claude Code, Codex
memory-systembojieli/ai-agent-bookSkill57k1mo agoApache-2.0A95Claude Code, Codex
release-helperSahir619/fable-methodSkill2.3k1mo agoMITA43Claude Code
loongsuite-pilot-insightalibaba/loongsuite-pilotSkill242yesterdayApache-2.0A111Claude Code, Codex