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 skills add DevelopersGlobal/ai-agent-skills --skill incremental-codinggit clone --depth 1 https://github.com/DevelopersGlobal/ai-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/developersglobal/ai-agent-skills/incremental-coding)<a href="https://agentmods.dev/skills/developersglobal/ai-agent-skills/incremental-coding"><img src="https://agentmods.dev/badge/skills/developersglobal/ai-agent-skills/incremental-coding/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.
<a href="https://agentmods.dev/skills/developersglobal/ai-agent-skills/incremental-coding"><img src="https://agentmods.dev/badge/skills/developersglobal/ai-agent-skills/incremental-coding.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00030 | $0.00537 |
| Opus 5.5 | $0.00012 | $0.00215 |
| Sonnet 5.5 | $0.00006 | $0.00107 |
| Haiku 4.5 | $0.00003 | $0.00054 |
Grade A, and why
incremental-coding 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
The biggest risk in software development is building a lot of code that doesn't work. Incremental coding limits this risk: build a little, verify it works, build more. At every step, the system is in a known-good state.
When to Use
- Any implementation that will take more than 2 hours
- When building in a complex domain you're uncertain about
- When multiple components need to integrate
Process
Step 1: Define the First Increment
- What is the smallest possible thing you can build that provides value and can be verified?
- It doesn't have to be feature-complete — just correct and verifiable.
- Example: "Add the endpoint skeleton with hardcoded response" before adding business logic.
Verify: The first increment can be verified in under 5 minutes.
Step 2: Build → Verify → Commit
- Build only the first increment.
- Run tests. Verify manually if needed. Confirm it works.
- Commit this working state.
- Repeat for the next increment.
Verify: There is a working commit after each increment.
Step 3: Integration Continuously
- Integrate with the real system as early as possible — not at the end.
- Test against real dependencies (DB, API, etc.) as early as possible.
- Fake integrations (mocks) should be replaced with real ones by the end.
Verify: By completion, all mocks replaced with real integration.
Common Rationalizations (and Rebuttals)
| Excuse | Rebuttal |
|---|---|
| "I need to build it all to know if it works" | No. Build the first piece and test it. Uncertainty is always reducible. |
| "Integration is at the end" | Integration pain is proportional to time since last integration. Integrate continuously. |
Verification
- Implementation built in verifiable increments
- Working commit exists after each increment
- No long stretches of "broken" state in git history
- All mocks replaced with real integrations by completion
References
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.
- 1mo ago First seen · 64 lines · 30 tokens per session scan A 0a252b683d93
incremental-coding is a skill published in the GitHub repository DevelopersGlobal/ai-agent-skills (177 stars, last pushed 5mo ago), licensed MIT. It adds 30 tokens to every session and 537 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 2026-08-30.
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git-workflow-and-versioning
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Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
performance-optimization
Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.
spec-driven-development
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