Borrowing it
Nothing to install: this file belongs to nvandessel/floop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nvandessel/floop/main/AGENTS.mdgit clone --depth 1 https://github.com/nvandessel/floopWrote 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/instructions/nvandessel/floop/agents-md)<a href="https://agentmods.dev/instructions/nvandessel/floop/agents-md"><img src="https://agentmods.dev/badge/instructions/nvandessel/floop/agents-md/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/instructions/nvandessel/floop/agents-md"><img src="https://agentmods.dev/badge/instructions/nvandessel/floop/agents-md.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 | $0.03483 | $0.03483 |
| Opus 5.5 | $0.01393 | $0.01393 |
| Sonnet 5.5 | $0.00697 | $0.00697 |
| Haiku 4.5 | $0.00348 | $0.00348 |
Grade A, and why
floop AGENTS.md 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 — 428 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Floop - Agent Instructions
For floop contributors. If you're a user, see docs/integrations/ for setup guides.
Floop Integration (REQUIRED)
You have persistent memory via floop. Learned behaviors are loaded via MCP and, where supported, auto-injected via hooks.
When corrected, IMMEDIATELY capture it:
mcp__floop__floop_learn(right="what to do instead")
# With optional context about what went wrong:
mcp__floop__floop_learn(right="what to do instead", wrong="what you did (optional)")
# With explicit tags (optional, for pack filtering):
mcp__floop__floop_learn(right="what to do instead", tags=["topic", "category"])
Do NOT wait for permission. Capture learnings proactively. The hooks will also auto-detect corrections, but explicit capture is more reliable.
For non-Claude agents, see docs/integrations/agent-prompt-template.md.
Available MCP tools:
floop_active- See currently active behaviors for this contextfloop_learn- Capture a correction (USE PROACTIVELY)floop_feedback- Signal whether a behavior was helpful (confirmed) or contradicted (overridden)floop_list- List all stored behaviorsfloop_deduplicate- Merge duplicate behaviors
Codex Runtime Cadence (No Lifecycle Hooks)
In Codex environments, treat these as required pseudo-hooks:
- Task start: Call
floop_activewith currentfileandtask. - Context change (file/task/mode shift): Re-call
floop_active. - Correction received: Immediately call
floop_learn(no permission needed). - Behavior outcome: Call
floop_feedbackwithconfirmedoroverridden.
If MCP is unavailable, use CLI fallback immediately:
floop active --file <path> --task <task> --json
floop learn --right "what to do instead" --wrong "what happened" --file <path>
floop list --json
Project Overview
floop is a CLI tool that enables AI agents to learn from corrections and maintain consistent behavior across sessions.
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 · 428 lines · 3,483 tokens per session scan A a120bf808602
floop AGENTS.md is an instructions file published in the GitHub repository nvandessel/floop (26 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 3,483 tokens to every session, about $0.0139 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 2026-08-30.
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