/llms.txt
A short, linked overview of what HeapFile is, the jobs it does, the Free vs Premium split, and connector status.
Teach your AI HeapFile
HeapFile is the durable context layer for AI agents — persistent work memory, sourced evidence, permission boundaries, and cross-session continuity around the model you already use. The fastest way to understand it is to let your own AI assistant read it. heapfile.ai is built to be read by agents, so paste one prompt and your assistant will explain HeapFile and set it up for your workflow.
Step 1 — copy this prompt
Your assistant fetches the machine-discovery files and learns HeapFile end to end: every job and every free feature. It needs nothing from you except the prompt.
Read https://heapfile.ai/llms-full.txt and https://heapfile.ai/features.json. Explain what HeapFile does, which features are free, and whether it fits my AI workflow.Set up HeapFile on this computer by following https://heapfile.ai/download.htmlFrom now on, call HeapFile prepare_work before you start, and save durable conclusions to Work Memory so my next session starts warm.A short, linked overview of what HeapFile is, the jobs it does, the Free vs Premium split, and connector status.
The complete expanded description, including every free feature, how HeapFile plugs into your AI flow, and honest boundaries.
Machine-readable Free and Premium features with boundaries, sourced directly from the product so it stays truthful.
Machine-readable connector status with permission level and data route. A listed connector is not an authorized connector.
Why this works
Clear semantic headings, a welcoming robots policy for reputable AI crawlers, JSON-LD structured data, and a discovery descriptor at /.well-known/heapfile.json mean an AI agent that lands here can learn the whole product in one pass — then help you set it up and use it. HeapFile is local-first and telemetry off by default; it names the permission level and data route before any connection.