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 thaitype/chief --skill loop-preflightgit clone --depth 1 https://github.com/thaitype/chiefWrote 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/thaitype/chief/loop-preflight)<a href="https://agentmods.dev/skills/thaitype/chief/loop-preflight"><img src="https://agentmods.dev/badge/skills/thaitype/chief/loop-preflight/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/thaitype/chief/loop-preflight"><img src="https://agentmods.dev/badge/skills/thaitype/chief/loop-preflight.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 | $0.00104 | $0.00748 |
| Opus 5.5 | $0.00042 | $0.00299 |
| Sonnet 5.5 | $0.00021 | $0.00150 |
| Haiku 4.5 | $0.00010 | $0.00075 |
Grade A, and why
loop-preflight 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loop preflight
loop-readiness reviews a plan's feedback mechanisms statically — it can confirm a
gate script is described in the plan, but by its own rule it never executes anything, so
it can't confirm the gate still actually runs. This skill fills that gap: it runs the
plan's existing feedback mechanisms for real, once, before the loop starts.
A gate can be described accurately in the plan and still be broken — an unrelated change landing between when the plan was written and when the loop actually starts can silently break something the plan assumes still works (e.g. a hardcoded path getting renamed elsewhere). Only actually running the check reveals that; a static read of the plan cannot.
This is a standalone check. Run it whenever a loop depends on pre-existing feedback,
whether or not loop-readiness was run first — loop-readiness's own report should
point here when it finds feedback the plan treats as already in place.
Step 1: Identify
From the plan (or a list the user gives directly), identify the concrete commands that are pre-existing verification the plan depends on — gate scripts, test suites, lint/type checks cited as feedback. This does not include the loop's actual work (deploy steps, migrations, code changes) — only the checks that trigger these to feedback about plan-driven work already have to keep passing.
List the identified commands back to the user before running anything. Don't assume; confirm the list is right and complete.
Step 2: Guardrails, then run
Before running each confirmed command:
- Scope check — only run commands identified in Step 1 as pre-existing feedback. Never run anything else from the plan (a deploy step, a migration, a data write) even if it's nearby in the same file or the user's earlier go-ahead was general.
- Production check — if a command's path, arguments, or target look
production-related (e.g. references something named
prod, or a shared/live system), stop and confirm with the user specifically before running that one — even if they already agreed to run the batch as a whole. A general "yes, run them" from Step 1 isn't informed consent for a specific command that turns out to touch something live.
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 · 61 lines · 104 tokens per session scan A f14dcb7d21da
loop-preflight is a skill published in the GitHub repository thaitype/chief (68 stars, last pushed 1mo ago), licensed MIT. It adds 104 tokens to every session and 748 once invoked, about $0.0004 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 2026-09-14.
loop-preflight compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| loop-preflightthaitype/chief | Skill | 68 | 1mo ago | MIT | A | 104 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |