inc-impl

A method for making software changes in small, complete slices. Each slice is implemented, tested, checked, and committed before the next one begins.

In plain words
What is it for?
Implementing features, refactoring code, and handling changes that span several files while keeping the project working throughout.
Why use it?
It reduces the risk of large multi-file changes becoming difficult to test or repair.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/thangchung/agent-engineering-experiment/inc-impl
Any agent
npx skills add thangchung/agent-engineering-experiment --skill inc-impl
Clone the repo
git clone --depth 1 https://github.com/thangchung/agent-engineering-experiment

Made for: Claude Code, Codex.

Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,939 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 88% copy Near-identical to another mod 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 $0.00051 $0.01939
Opus 5 $0.00026 $0.00970
Sonnet 5 $0.00010 $0.00388
Haiku 4.5 $0.00005 $0.00194

Measured 3d ago against content hash f37ce73debbd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

inc-impl 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 3d 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.

Origin

This is a copy

88% identical to incremental-implementation — 21 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

foundry-agentfx/.github/skills/inc-impl/SKILL.md · 245 lines

How it starts

The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Incremental Implementation

Overview

Build in thin vertical slices — implement one piece, test it, verify it, then expand. Avoid implementing an entire feature in one pass. Each increment should leave the system in a working, testable state. This is the execution discipline that makes large features manageable.

When to Use

  • Implementing any multi-file change
  • Building a new feature from a task breakdown
  • Refactoring existing code
  • Any time you're tempted to write more than ~100 lines before testing

When NOT to use: Single-file, single-function changes where the scope is already minimal.

The Increment Cycle

┌──────────────────────────────────────┐
│                                      │
│   Implement ──→ Test ──→ Verify ──┐  │
│       ▲                           │  │
│       └───── Commit ◄─────────────┘  │
│              │                       │
│              ▼                       │
│          Next slice                  │
│                                      │
└──────────────────────────────────────┘

For each slice:

  1. Implement the smallest complete piece of functionality
  2. Test — run the test suite (or write a test if none exists)
  3. Verify — confirm the slice works as expected (tests pass, build succeeds, manual check)
  4. Commit -- save your progress with a descriptive message (see git-workflow-and-versioning for atomic commit guidance)
  5. Move to the next slice — carry forward, don't restart

Slicing Strategies

Vertical Slices (Preferred)

Build one complete path through the stack:

Slice 1: Create a task (DB + API + basic UI)
    → Tests pass, user can create a task via the UI

Slice 2: List tasks (query + API + UI)
    → Tests pass, user can see their tasks

Slice 3: Edit a task (update + API + UI)
    → Tests pass, user can modify tasks

Slice 4: Delete a task (delete + API + UI + confirmation)
    → Tests pass, full CRUD complete

Each slice delivers working end-to-end functionality.

Read the full file on GitHub · 245 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. 3d ago First seen · 245 lines · 51 tokens per session scan A f37ce73debbd

Subscribe to this mod's changes

inc-impl is a skill published in the GitHub repository thangchung/agent-engineering-experiment (24 stars, last pushed 1mo ago), licensed MIT. It adds 51 tokens to every session and 1,939 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to incremental-implementation, differing in 21 lines, and is treated as a copy.

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