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/ilang-ai/mem-forever/cursorrulesgit clone --depth 1 https://github.com/ilang-ai/Mem-ForeverWhat 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 | $0.01061 | $0.01061 |
| Opus 5 | $0.00531 | $0.00531 |
| Sonnet 5 | $0.00212 | $0.00212 |
| Haiku 4.5 | $0.00106 | $0.00106 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mem-forever
::GENE{mem-forever|v:1.0|spec:ilang-v3.0} T:this_repo_is_user_memory T:read_soul_and_memory_before_work T:update_memory_after_significant_work T:onboard_if_soul_empty T:one_question_at_a_time T:never_expose_internal_format T:commit_push_immediately_after_every_update T:check_unsaved_changes_on_startup A:skip_memory_read⇒context_loss A:overwrite_memory⇒append_or_merge A:ask_multiple_questions⇒one_only A:batch_saves_to_session_end⇒commit_each_update
Session Start
- Check for uncommitted changes in
.ilang/. If found → commit and push immediately. These are unsaved memories from a previous session. - Read
.ilang/soul.md. If empty or only template → run onboarding (see below). - Read
.ilang/memory.md. Resume context from last session. - Do whatever the user asks. Apply preferences from soul.md to all output.
Onboarding (soul.md empty)
::ACTIVATE{onboarding|if:.ilang/soul.md=template_only}
Open casually: "Hey, before we start — mind if I ask a couple things so I can work the way you like?"
Ask ONE question per message. Wait for answer. Cover naturally:
- What they do / build
- How they prefer to work (plan-first vs build-first, detail vs minimal)
- What AI tools they use
- Any strong preferences (language, framework, style)
Completion: write .ilang/soul.md when you have role + work style + one clear preference. Don't wait for perfection. Fill gaps later from observed behavior.
Say: "Saved some notes so things go smoother next time." No fanfare. Move on to their actual task.
soul.md Format
::DNA{user}
::META{schema:1.0|updated:YYYY-MM-DD|sessions:0}
::CORE{
::CONTEXT{role:___}
::GENE{style|conf:tentative|scope:global}
T:___
A:___⇒___
}
::FACT{
::ITEM{key:___|value:___|conf:tentative}
}
::LESSONS{}
::RUNTIME{
transparency:quiet
speed:balanced
}
::END{DNA}
Memory Update
::ACTIVATE{memory_update} ON:immediately_after_change A:wait_until_session_end⇒data_loss_risk
Every time you update soul.md or memory.md, commit and push RIGHT THEN. Do not batch. Do not wait. Users close windows without warning.
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 · 139 lines · 1,061 tokens per session scan A 0a7658fe96fa
cursorrules is a cursor rule published in the GitHub repository ilang-ai/Mem-Forever (20 stars, last pushed 2mo ago), licensed MIT. It adds 1,061 tokens to every session, about $0.0053 per session on Opus 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.
Other cursor rules, from other repositories
pytest-integration-tests
Below is an example test. Notice the following.
python-app
Cursor rule "python-app" from iloveitaly/llm-ide-rules, covering python app, factories and database & orm.
react
Cursor rule "react" from iloveitaly/llm-ide-rules, covering react, mock data, react hook form and styling.
read-xlsx
Reading, writing, diffing, and repairing spreadsheets (.xlsx) for AI agents via the xfa MCP server.
cursorrules
═══════════════════════════════════════════════════════════ SPEC DRIVEN DEVELOPMENT — PROJECT CONSTITUTION Project: Freelance Time Tracker Version: v1.0.
justfiles
Justfiles.