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/vanja-emichi/a0_agent_skills/incremental-implementationnpx skills add vanja-emichi/a0_agent_skills --skill incremental-implementationgit clone --depth 1 https://github.com/vanja-emichi/a0_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/vanja-emichi/a0_agent_skills/incremental-implementation)<a href="https://agentmods.dev/skills/vanja-emichi/a0_agent_skills/incremental-implementation"><img src="https://agentmods.dev/badge/skills/vanja-emichi/a0_agent_skills/incremental-implementation.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 | $0.00052 | $0.02201 |
| Opus 5 | $0.00026 | $0.01100 |
| Sonnet 5 | $0.00010 | $0.00440 |
| Haiku 4.5 | $0.00005 | $0.00220 |
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 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.
This is a copy
84% identical to incremental-implementation — 65 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.
How it starts
The opening of the file, as written. The whole thing — 287 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:
- Implement the smallest complete piece of functionality
- Test — run the test suite using
code_execution_tool(or write a test if none exists) - Verify — confirm the slice works as expected (tests pass, build succeeds, manual check)
- Commit — save your progress with a descriptive message (see
git-workflow-and-versioningfor atomic commit guidance; load withskills_tool:load skill_name=git-workflow-and-versioning) - 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
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 · 287 lines · 52 tokens per session scan A 6323468c4244
incremental-implementation is a skill published in the GitHub repository vanja-emichi/a0_agent_skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 2,201 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to incremental-implementation, differing in 65 lines, and is treated as a copy.
Other skills, from other repositories
ai-loop
Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.
project-execution
Executes implementation plans with progress tracking, checkpoint validation, and quality gates. Use after planning is complete and tasks are ready to implement.
refactoring-workflow
Improve the structure of existing code without changing its behaviour, in small verified steps under a green test suite. Use when the user asks to refactor, clean up, restructure or simplify code, wants to reduce duplication or coupling, is preparing a codebase for a feature it cannot currently accommodate, or when…
absolute-simplify
Use when the user wants to simplify, clean up, refactor, tidy, or refine code — their staged/unstaged git changes or a target file/path. Reduces complexity, flattens nesting, removes redundancy and dead code, scores each change by value (holding low-value churn), then runs tests to prove nothing broke. Invoke on…
refactoring
Safe, test-backed code restructuring in small steps.
pipeline-optimizer
Structured 6-step procedure for improving, renovating, or rebuilding existing pipelines, individual project folders, documentation structures, or software stacks. Addressable as "pipeline optimizer" (for whole topic pipelines, e.g. a software, research, or game-dev pipeline) or "project-folder optimizer" (for…