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/ScienceIsNeato/slop-mopWrote 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/scienceisneato/slop-mop/sm-refit)<a href="https://agentmods.dev/commands/scienceisneato/slop-mop/sm-refit"><img src="https://agentmods.dev/badge/commands/scienceisneato/slop-mop/sm-refit.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 5.1 | $0.00000 | $0.00165 |
| Opus 5 | $0.00000 | $0.00082 |
| Sonnet 5 | $0.00000 | $0.00033 |
| Haiku 4.5 | $0.00000 | $0.00016 |
Grade A, and why
sm-refit 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 6d 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
/sm-refit
Run slop-mop's one-time onboarding remediation rail for this repository.
- For an existing repo that has not been remediated, start with
sm refit --start. - Fix the current gate or blocker it reports.
- Run
sm refit --iterateto resume the stored plan. - Repeat until the plan is complete, then run
sm refit --finish.
This is step 0 for inherited or already-messy repositories. Let refit own the structured remediation plan and commits; use the swab/scour/buff loop after the repo has entered maintenance.
Prerequisite: sm must be installed. If command not found, suggest:
pipx install slopmop[all]
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.
- 6d ago First seen · 17 lines · 0 tokens per session scan A c3415a7671a1
sm-refit is a command published in the GitHub repository ScienceIsNeato/slop-mop (6 stars, last pushed 17d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 165 tokens. 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
patrol-on
Force patrol mode on for this session — enables investigation gate and band-aid detection.
cloudflare-durable-objects:migrate
Interactive Durable Objects migration assistant. Guides through new class creation, renaming, deletion, and transfer migrations with validation.
cloudflare-durable-objects:optimize
Interactive Durable Objects performance optimization assistant. Analyzes existing DO code and provides specific optimization recommendations with implementation guidance.
cloudflare-workers:debug
Interactive debugging workflow for Cloudflare Workers. Diagnoses deployment errors, runtime issues, and performance problems with step-by-step fixes.
cloudflare-queues:troubleshoot
Quick troubleshooting for common Cloudflare Queues issues.
cloudflare-workflows:debug
Interactive debugging for failing workflow instances. Use when user reports workflow errors, instances stuck, or deployment failures.