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 rules/arango-solutions/arango-sparql-py/incremental-over-atomicgit clone --depth 1 https://github.com/arango-solutions/arango-sparql-pyWrote 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/rules/arango-solutions/arango-sparql-py/incremental-over-atomic)<a href="https://agentmods.dev/rules/arango-solutions/arango-sparql-py/incremental-over-atomic"><img src="https://agentmods.dev/badge/rules/arango-solutions/arango-sparql-py/incremental-over-atomic.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 | $0.00390 | $0.00390 |
| Opus 5 | $0.00195 | $0.00195 |
| Sonnet 5 | $0.00078 | $0.00078 |
| Haiku 4.5 | $0.00039 | $0.00039 |
Grade A, and why
incremental-over-atomic 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 4d 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.
What it actually says
Incremental Over Atomic
"Small steps that individually work > Large steps that eventually work."
Big-bang changes are high-risk gambles. Incremental changes are safe, reviewable, and reversible.
Instead of Big Bang → Incremental Slices
| Big Bang | Incremental |
|---|---|
| Refactor entire module at once | Refactor one function, verify, commit, repeat |
| Add feature + tests + docs in one PR | Types first → logic → tests → docs |
| Replace old system with new | Run both in parallel, migrate gradually, remove old |
Each Increment Must Be
- Verifiable — can be tested independently
- Reversible — can be rolled back without affecting other changes
- Reviewable — small enough to understand in < 5 minutes
- Deployable — doesn't break the build in isolation
If an increment takes more than 30 minutes, slice smaller.
The Working State Rule
At every checkpoint, the codebase MUST: compile, pass tests, be functional.
Refactoring Pattern
# GOOD: Incremental
1. Add new function alongside old → verify (commit)
2. Migrate one caller → verify (commit)
3. Repeat until all callers migrated
4. Remove old function (commit)
Anti-Pattern Detector
- Changing more than 5 files at once → Slice smaller
- Working 1+ hour without a commit → Checkpoint now
- Unable to describe the change in one sentence → It's too big
- Afraid to run tests because "it's not done yet" → You've gone too far
Small steps. Verify each one. Never break the build.
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.
- 4d ago First seen · 51 lines · 390 tokens per session scan A bd8fc83ac059
incremental-over-atomic is a cursor rule published in the GitHub repository arango-solutions/arango-sparql-py (2 stars, last pushed 17d ago), licensed MIT. It adds 390 tokens to every session, about $0.0019 per session on Opus 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.
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