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.
git clone --depth 1 https://github.com/affectionatec/agentic-engineeringWrote 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/commands/affectionatec/agentic-engineering/run-loop)<a href="https://agentmods.dev/commands/affectionatec/agentic-engineering/run-loop"><img src="https://agentmods.dev/badge/commands/affectionatec/agentic-engineering/run-loop/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/commands/affectionatec/agentic-engineering/run-loop"><img src="https://agentmods.dev/badge/commands/affectionatec/agentic-engineering/run-loop.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 | $0.00050 | $0.00173 |
| Opus 5.5 | $0.00020 | $0.00069 |
| Sonnet 5.5 | $0.00010 | $0.00035 |
| Haiku 4.5 | $0.00005 | $0.00017 |
Grade A, and why
run-loop 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.
What it actually says
Invoke the agentic-engineering:run-loop skill with this target: $ARGUMENTS
The skill carries the full loop protocol — target parsing, preconditions, the per-task loop body, stop conditions, wind-down, and hard rules. Follow it exactly. (This command is a thin alias so /run-loop works in Claude Code; the skill is the single source of truth and also serves harnesses that load skills but not plugin commands.)
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 · 9 lines · 0 tokens per session scan A e72e50db8cd4
run-loop is a command published in the GitHub repository affectionatec/agentic-engineering (5 stars, last pushed 3mo ago), licensed MIT. It adds 50 tokens to every session and 173 once invoked, about $0.0002 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 2026-08-31.
Other commands, from other repositories
release-update
(dev-only) release-update maintainer harness — Claude Code upstream change tracker (release-notes version-delta sweep + docs sync). NOT distributed to user projects.
release
(dev-only) release maintainer harness — MoAI-ADK production release (git-flow: rc build on develop, release/vX.Y.Z cut from develop, PR to main, scripts/release.sh + GoReleaser, back-merge into develop). NOT distributed to user projects.
ticket
Take a GitHub issue through an isolated implementation and pull request in its own Herdr tab.
commit
Stage and commit changes with a well-written message.
pr
Push the current branch and open a pull request.
squash
Squash recent commits into a single clean commit.