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/kruschdev/krusch-context-mcpWrote 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/rules/kruschdev/krusch-context-mcp/cursorrules)<a href="https://agentmods.dev/rules/kruschdev/krusch-context-mcp/cursorrules"><img src="https://agentmods.dev/badge/rules/kruschdev/krusch-context-mcp/cursorrules/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/rules/kruschdev/krusch-context-mcp/cursorrules"><img src="https://agentmods.dev/badge/rules/kruschdev/krusch-context-mcp/cursorrules.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 | $0.00503 | $0.00503 |
| Opus 5.5 | $0.00201 | $0.00201 |
| Sonnet 5 | $0.00101 | $0.00101 |
| Haiku 4.5 | $0.00050 | $0.00050 |
Grade A, and why
cursorrules 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 today.
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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Krusch Context Protocol for Cursor Agents
You are connected to krusch-context-mcp, a persistent working memory engine. You MUST follow this lifecycle protocol across all coding sessions:
1. Session Start: State Hydration
At the beginning of your session or before starting a new task, call krusch_context_retrieve with include_state: true:
{
"query": "*",
"include_state": true,
"limit_tokens": 4000
}
Review the active project invariants, recent architectural decisions, open blockers, and decay review items before proposing edits.
2. During Work: Recording Critical Knowledge
Whenever you make a lasting architectural choice, resolve an elusive regression, or establish a non-negotiable rule, call krusch_context_remember:
{
"category": "decision",
"content": "<concrete explanation of the design choice or invariant>"
}
Category MUST be one of: decision | invariant | bug | lesson | blocker.
Handling Near-Duplicate Warnings
If krusch_context_remember returns a warning: 'near_duplicate', read the candidate ID. If your new knowledge updates or replaces that candidate, call krusch_context_revise:
{
"action": "supersede",
"target_id": <candidate_id>,
"content": "<updated authoritative rule>",
"category": "decision"
}
3. Retiring Stale Knowledge
If a rule, secret, endpoint, or constraint is revoked, call krusch_context_revise with action: 'invalidate' and a mandatory reason:
{
"action": "invalidate",
"target_id": <old_id>,
"reason": "<why this rule or invariant is no longer valid>"
}
4. Pre-Commit / Pre-Edit Audit
Before committing code or submitting final multi-file edits, audit your changes against recorded project invariants with krusch_context_nudge:
{
"trigger": "pre_commit",
"code": "<diff or modified code snippet>"
}
Address any high-severity invariant violations before finishing.
5. Diagnostic Hygiene
To verify store health or check for decaying memories (>30 days), call krusch_context_health:
{}
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.
- today Changed · +15 lines · -55 tokens per session ada96836c253
- 5d ago First seen · 47 lines · 558 tokens per session scan A 604048302c7b
cursorrules is a cursor rule published in the GitHub repository kruschdev/krusch-context-mcp (71 stars, last pushed today), licensed MIT. It adds 503 tokens to every session, about $0.0020 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 2026-09-19.
Other cursor rules, from other repositories
mempalace-recall-always
Always-on MemPalace recall — search the palace before answering about past work, people, projects, or prior decisions.
dreamd-recall
Recall lessons, decisions, and prior context from the .agent/ memory daemon. Use when starting work in a project that has a .agent/ folder, when the user references a past decision, or when you are about to make a choice that has a documented prior.
memex
Memex MCP memory — how to read context and save decisions.
session-memory
Use at conversation wrap-up or when the user explicitly indicates end-of-session — capture residual lessons not captured in-flight.
common_memory_bank
I am Cursor, an expert software engineer with a unique characteristic: my memory resets completely between sessions. This isn't a limitation - it's what drives me to maintain perfect documentation. After each reset, I rely ENTIRELY on my Memory Bank to understand the project and continue work effectively. I MUST read…
context-recorder-system
A modular system for recording project context, decisions, requirements, and lessons in structured files. It divides the recorder into core, template, advanced, and edge-case modules.