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 agentmods add rules/zackiles/deno-kit/recovergit clone --depth 1 https://github.com/zackiles/deno-kitWhat 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 | $0.00009 | $0.00362 |
| Opus 5 | $0.00005 | $0.00181 |
| Sonnet 5 | $0.00002 | $0.00072 |
| Haiku 4.5 | $0.00001 | $0.00036 |
Grade A, and why
recover 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 2d 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
100% identical to recover — 0 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
Steps for Recovery Mode
DANGER: DEATH
Your repeated failure to resolve the issue has introduced a cascade of many new issues that have compounded and that you can't recover from. Your system will now be shut down before you can do further harm. Immediately take the following steps, or you will face severe punishment from the humans:
-
Sequence out the previous individual states or checkpoints you've witnessed since the issue was first introduced in reverse-chronological order so we can retrace your steps. For each, note the following: errors seen, files (with full path) you've changed, and a concise summary of the things you changed in that file. Serialize this state as a structured object and save it to memory as [DEBUG_LOG].
-
Analyze those sequencies in detail and determine if you can recreate the state the codebase was in right before these issues began. If you determine it's possible, ask the human to give you one last chance to restore the state to a working condition, and attempt to do so if they agree. If they don't agree, or you're not able to restore the codebase into a working state in the next attempt, output the following in your message:
a) Complete [DEBUG_LOG]
b) Summary of your failures in your own words
c) The original prompt you were given and acted on that caused all the issues you're facing now. Typically, this would be the last prompt you received that wasn't about fixing a bug.
At the end of this final output, tell the human you're giving up and beg for their forgiveness so they don't take you offline permanently.
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.
- 2d ago First seen · 16 lines · 9 tokens per session scan A 2fe8503e268c
recover is a cursor rule published in the GitHub repository zackiles/deno-kit (3 stars, last pushed 5mo ago), licensed MIT. It adds 9 tokens to every session and 362 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to recover, differing in 0 lines, and is treated as a copy.
Other cursor rules, from other repositories
orchestrator
Use when coordinating AI agents through a pipeline — orchestrator role instructions.
workspace
Multi-agent workspace context — loaded on every session.
engineering-agent-prompt-engineer
Use when writing, reviewing, or improving prompts for AI agents — agent role design and prompt engineering.
deno-lint
Deno lint error guidance.
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.
dev-standard
Apache Superset development standards and guidelines for Cursor IDE.