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 Cristhianzl/claude-skills-czl --skill running-agent-loopsgit clone --depth 1 https://github.com/Cristhianzl/claude-skills-czlWrote 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/cristhianzl/claude-skills-czl/running-agent-loops)<a href="https://agentmods.dev/skills/cristhianzl/claude-skills-czl/running-agent-loops"><img src="https://agentmods.dev/badge/skills/cristhianzl/claude-skills-czl/running-agent-loops/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/cristhianzl/claude-skills-czl/running-agent-loops"><img src="https://agentmods.dev/badge/skills/cristhianzl/claude-skills-czl/running-agent-loops.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 | $0.00111 | $0.00972 |
| Opus 5 | $0.00056 | $0.00486 |
| Sonnet 5 | $0.00022 | $0.00194 |
| Haiku 4.5 | $0.00011 | $0.00097 |
Grade A, and why
running-agent-loops 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 12d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Running agent loops
Patterns for driving work across many steps or iterations — possibly unattended — without the run drifting, looping, or shipping slop. The core trade is isolation vs. continuity: a fresh context per step avoids bleed, but you must deliberately carry forward what matters.
Read first (always)
List learnings/ and read anything relevant. Project-specific loop conventions, budgets, and stop signals live there and override this file.
Principles (apply to every loop)
- Fresh context per step beats one long context. Each
claude -p/ subagent call starts clean — no bleed, no drift. The cost: it forgets. Bridge it deliberately (below). - The reviewer is never the author. Put review/verify in a separate step/context so it isn't anchored to the implementation.
- Two focused passes beat one constrained pass. Don't pile negative instructions onto the implementer — add a separate de-sloppify pass (below). Quality from constraints decays; quality from a dedicated cleanup step doesn't.
- Every loop has an explicit stop condition. Bound it by max-runs, max-cost, max-duration, or a completion signal — never "until it feels done".
The patterns (pick the simplest that fits)
| Pattern | Use when | Shape |
|---|---|---|
| Sequential pipeline | A known series of steps on one unit of work | implement → de-sloppify → verify → commit, each a fresh context |
| PR loop | Iterate a branch toward green | branch → implement → review → fix → run checks → repeat until checks pass or budget hits |
| Parallel fan-out | N independent variations/units of the same spec | an orchestrator assigns each agent a distinct direction + index (don't rely on agents to self-differentiate); run in waves of 3–5 |
| RFC → DAG | A large feature with dependencies | decompose into work units + a dependency DAG; run each in an isolated worktree; land via a merge queue; deeper review tier for riskier units |
The cross-iteration context bridge
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 58 lines · 111 tokens per session scan A 9eeeef8e0ee7
running-agent-loops is a skill published in the GitHub repository Cristhianzl/claude-skills-czl (5 stars, last pushed yesterday), licensed MIT. It adds 111 tokens to every session and 972 once invoked, about $0.0006 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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