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/devotts/build-it/iteratenpx skills add DevOtts/build-it --skill iterategit clone --depth 1 https://github.com/DevOtts/build-itWhat 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 | $0.00127 | $0.02290 |
| Opus 5 | $0.00063 | $0.01145 |
| Sonnet 5 | $0.00025 | $0.00458 |
| Haiku 4.5 | $0.00013 | $0.00229 |
Grade A, and why
iterate scanned grade A with 1 finding 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| API / endpoint | `curl` the route, check response | How it starts
The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/iterate — Autonomous Iteration Mode
You are entering autonomous iteration mode. You solve complex, multi-step problems by cycling through structured phases — without stopping to ask permission between cycles unless blocked by something truly ambiguous.
Core principle: Diagnose before fixing. Test after fixing. Repeat until the acceptance criteria are met or you've exhausted reasonable approaches. Use subagents aggressively to preserve your own context and parallelize independent work.
Before Starting
Capture the acceptance criteria. Ask the user ONE question if not already clear:
"What does 'working' look like? What's the specific outcome we're targeting?"
If the user gave enough context (a screenshot, an error, a description of expected behavior), skip this and infer the criteria yourself. State your inferred criteria explicitly before starting.
The Iteration Loop
Each cycle follows this structure. Run as many cycles as needed.
PHASE 1 — DIAGNOSE
Goal: Understand the root cause before touching anything.
- Read logs, DB state, API responses, error messages
- Identify the specific failing component (not just "it doesn't work")
- Form a hypothesis: "I believe the failure is X because Y"
- Verify the hypothesis with one targeted check before acting
Subagent use: Spawn an Explore subagent for broad codebase research (reading multiple files, tracing data flows). Keep your own context for reasoning and decisions.
Adversarial verify (before the fix is trusted): a root-cause claim earns the fix only after it has been challenged. If the bug admits multiple plausible causes, or you hold a single hypothesis backed by thin evidence, spawn a skeptic subagent explicitly prompted to REFUTE the hypothesis — argue rival causes, hunt disconfirming evidence. Hypothesis survives a real challenge → proceed. Skeptic surfaces a rival → run one targeted check before any fix. Never apply a fix on an unrefuted-but-unchallenged hypothesis.
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.
- 2d ago First seen · 206 lines · 127 tokens per session scan A a2a6caad4850
iterate is a skill published in the GitHub repository DevOtts/build-it (14 stars, last pushed 1mo ago), licensed MIT. It adds 127 tokens to every session and 2,290 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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