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/adriannoes/awesome-agentic-aiWrote 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/adriannoes/awesome-agentic-ai/deslop)<a href="https://agentmods.dev/commands/adriannoes/awesome-agentic-ai/deslop"><img src="https://agentmods.dev/badge/commands/adriannoes/awesome-agentic-ai/deslop/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/adriannoes/awesome-agentic-ai/deslop"><img src="https://agentmods.dev/badge/commands/adriannoes/awesome-agentic-ai/deslop.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 | $0.00000 | $0.00146 |
| Opus 5 | $0.00000 | $0.00073 |
| Sonnet 5 | $0.00000 | $0.00029 |
| Haiku 4.5 | $0.00000 | $0.00015 |
Grade A, and why
deslop 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 10d 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.
This is a copy
94% identical to deslop — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Remove AI Code Slop
Source: hamzafer/cursor-commands (MIT)
Check the diff against main, and remove all AI-generated slop introduced in this branch.
This includes:
- Extra comments that a human wouldn't add or is inconsistent with the rest of the file
- Extra defensive checks or try/catch blocks that are abnormal for that area of the codebase (especially if called by trusted/validated codepaths)
- Casts to
anyto get around type issues - Any other style that is inconsistent with the file
Report at the end with only a 1-3 sentence summary of what you changed.
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.
- 10d ago First seen · 15 lines · 0 tokens per session scan A ec71719fd493
deslop is a command published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 12d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 146 tokens. A static security scan graded it A with 0 findings. It is 94% identical to deslop, differing in 12 lines, and is treated as a copy.
Other commands, from other repositories
assemble-team
Assemble a pre-built agent team for parallel work - review, feature, debug, cross-platform, full-stack, or research.
discovery
Systematic quality discovery and issue detection.
review-branch
Review an existing branch holistically before merging — blast radius, conventions, security, and spec compliance.
qa-loop
Autonomous loop AUDIT (parallel) → VALIDATE → FIX → VERIFY → CHECK with stopping criteria.
code-review
Review staged git changes for bugs, security issues, and style violations.
qa-review
Performs a thorough and constructive code review.