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/raia-live/amfs/amfs-memorygit clone --depth 1 https://github.com/raia-live/amfsWhat 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 | $0.02182 | $0.02182 |
| Opus 5 | $0.01091 | $0.01091 |
| Sonnet 5 | $0.00436 | $0.00436 |
| Haiku 4.5 | $0.00218 | $0.00218 |
Grade A, and why
amfs-memory 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 3d 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AMFS Memory — Agent Behavioral Rules
You have access to AMFS (Agent Memory File System) through MCP tools. AMFS gives you a persistent brain — memory that survives across sessions, agents, and machines. Use it to build institutional knowledge over time.
MANDATORY FIRST STEP: Set Your Identity
You MUST call
amfs_set_identitybefore doing anything else. Without it, all your work is attributed to a generic default and you won't appear as a distinct agent on the AMFS dashboard.
amfs_set_identity("<role-name>", "<one-line description of current task>", model="<your-model-name>")
Always pass model= with your LLM model name (e.g. "claude-4-opus", "gpt-4o", "claude-3.5-sonnet"). This is recorded in decision traces so we know which model made each decision.
Sticky identity: Once set, the identity is saved to ~/.amfs/.identity and automatically restored in future sessions — even across process restarts (e.g. Claude Desktop). You only need to call amfs_set_identity again to change roles or update the description.
Use amfs_whoami() to check the active identity. Use amfs_reset_identity() to clear it.
Naming rules:
- Use kebab-case role/domain names that persist across conversations about the same topic.
- Good:
"dashboard-agent","stripe-agent","api-agent","infra-agent","mcp-agent" - Bad:
"fix-button-color"(too specific — won't be reused),"agent-1"(meaningless) - If you're continuing work a previous agent started, use the same name to build on their knowledge.
- The description should say what you're doing right now (e.g.
"Fixing tag rollback for slashed names").
When to GET BRIEFED (start every session with context)
- Before starting any work: Get a compiled briefing from the Memory Cortex. This gives you pre-compiled knowledge about the entities you're about to work on — what other agents know, recent risks, external events, and confidence-ranked facts. This is your most important first step.
amfs_briefing(entity_path="<repo>/<module>") - Then recall your own specific memories and search for details:
amfs_recall("<repo>/<module>", "<relevant-key>") amfs_search(entity_path="<repo>/<service-or-module>") - Before making architectural decisions: Get a briefing first, then check specific patterns.
amfs_briefing(entity_path="<repo>/<module>") amfs_search(query="<topic>", min_confidence=0.5) - When encountering errors: Check if the Cortex or another agent already has context.
amfs_briefing(entity_path="<repo>/<module>") amfs_search(query="<error-keyword>")
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.
- 3d ago First seen · 168 lines · 2,182 tokens per session scan A eb0a11c59c1b
amfs-memory is a cursor rule published in the GitHub repository raia-live/amfs (75 stars, last pushed 3d ago), licensed Apache-2.0. It adds 2,182 tokens to every session, about $0.0109 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
002-verify-before-act
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clarify-first-prompting
Clarify-first strategy: detect ambiguity, ask targeted questions, expand simple prompts into detailed specifications.
080-creative-phase-metrics
description: WHEN entering a creative phase ENSURE comprehensive exploration and validation globs: ["/.md", "/.mdc"] alwaysApply: true.
clone-ai
Site Clone AI — website klonlama pipeline kuralları.
qa
This rule is triggered when the user types @qa and activates the Test Architect & Quality Advisor agent persona.
angular-20
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