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For AI assistants

Read first: Why Occam — advantages and knobs — honesty, token contract, ladder, receipts, and opt-in knobs in one page. Do not treat Occam as a generic web fetch.

Then the compact map — do not ingest the whole documentation site:

  • Repository: llms.txt — agent routing, capability-family index, experimental gates, operator surface, and trust limits
  • Docs site entry: this page + task router below

Then:

  1. Use the task router
  2. Open one focused tool page
  3. Open failure codes only after ok: false
  4. Open configuration only when setup is required
  5. Use MCP API only for normative response semantics
  6. For proof boundaries and name corrections (ok:false, receipts, claim_check, attest, crosscheck), read Handbook — honesty contract or the Trust limits section in llms.txt

Runtime tools/list wins for tool availability and input schemas.

Honesty defaults: ok:false means content is unknown. Receipts prove integrity relative to a key — not truth, origin, or trusted time. Crosscheck is multi-source comparison, not consensus proof. npm is not GA. Cosign on install is policy-gated (required-cosign-v1 for published 1.0.0-rc.3+, requires the cosign CLI; published v1.0.0-rc.2 remains SHA-256-only) and proves release authenticity/signer identity, not page-content truth. There is no public MCP codec / compression-algorithm selector — use materialization knobs on Why Occam.

For humans using an AI assistant

Paste a prompt like:

Read https://raw.githubusercontent.com/ContextForgeAI/occam/main/docs/why-occam.md and https://raw.githubusercontent.com/ContextForgeAI/occam/main/llms.txt. Treat Occam as honesty + token-budgeted extract (not generic fetch). Help me research these URLs: …

Or point the assistant at the docs site:

https://contextforgeai.github.io/occam/why-occam/

Future: docs-aware assistant

A hosted “Ask AI” search over this documentation may arrive later. Not shipped today. This navigation slot is reserved so we can add it without reorganizing the site.

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