LLMS-TLDR 0.2

/llms-tldr.txt is an optional experimental Cybermaps publication for testing deterministic, token-budgeted site briefings.

It is not part of the llms.txt proposal, an IETF standard, an MCP resource, an Agent Skill, a search index, or an AI-generated summary.

Stable order

  1. Configured pinned resource IDs in publisher order
  2. Configured content-type order
  3. Stored modified time descending
  4. WordPress object ID ascending

Literal extraction

Each candidate contains the title, public URL, content type, valid stored modification time, and a fixed-length literal extract.

Cybermaps strips stored markup but does not execute shortcodes or server-rendered dynamic blocks.

Whole-entry budgeting

The disclosed estimator is:

estimated_tokens = ceil(UTF-8 bytes / 4)

The configured range is 1,000–200,000 approximate tokens; the default is 80,000.

Cybermaps includes a candidate only when the complete entry and updated coverage header fit. An entry is never cut midway by the budgeter. The final header reports selected, eligible, omitted, and partial counts; partial remains zero in version 0.2.

Explicit non-features

The generator does not:

  • score quality;
  • infer entities;
  • cluster topics;
  • deduplicate meaning;
  • calculate information gain;
  • execute a model; or
  • claim downstream adoption.

Physical publication in all mode bypasses PHP and cannot be counted by Discovery Analytics.

The full technical rationale is available in the 0.2 draft paper.