Less webpage. More usable context.¶
Live URL → compact Markdown for AI agents — or a typed
ok:false. Strips chrome, fits a token budget, keeps the source.
Does not invent page text from model memory.
Webpage noise
<header>…</header>
<nav class="site-nav">…</nav>
<script src="bundle.js"></script>
<aside class="sidebar">…</aside>
<footer>…</footer>Source-linked Markdown
1 # Web context without the chrome
2
3 Agent infrastructure · 8 minute read
4
5 AI agents rarely need the whole
6 interface of a webpage. They need
7 the useful text, its structure, and
8 enough source information to explain
9 where the material came from.
10
11 ## The hidden cost of a page readsource: representative-input.html
- This demo · HTML
- 5,297 B
- This demo · Markdown
- 1,736 B
One inspectable demo page — not an average, not a promise. Real sites vary (sometimes much more chrome, sometimes almost none). Bytes, not tokens.
curl -fsSL https://raw.githubusercontent.com/ContextForgeAI/occam/main/scripts/get-ff-occam.sh | bash
occam connect): npx ff-occam@1.1.1.
What you get (30 seconds)¶
| Capability | |
|---|---|
| Honest read | Live extract → Markdown, or typed refusal. ok:false = content unknown. |
| Token contract | occam_client_capabilities, max_tokens, fit_markdown + focus_query — not an LLM summarizer. |
| Acquisition ladder | HTTP → browser when needed → typed refusal. |
| One page / many | occam_transcode · occam_digest · occam_map / occam_search. |
| Structure / diffs | Opt-in blocks/tables/feeds · if_none_match / diff_against. |
| Integrity | Optional Receipt v1 → occam_verify (integrity vs a key — not truth). |
| Playbooks | Per-site recipes when you author them. |
| Local-first | Runs with you; private URL / SSRF blocks by default. |
Full knobs and tool map: Why Occam. Agents: start at llms.txt.
Inspect one demo (not a benchmark)¶
The product claim is usable context or an honest unknown — not a fixed “% smaller” rate. Chromed marketing pages often shrink a lot; a clean docs page may barely shrink. We publish one stable fixture so you can open the input, run the same call, and check the method.
<header>…search…</header>
<nav>…repeated links…</nav>
<main>
<article>Web context without the chrome…</article>
<aside>…newsletter…related reading…</aside>
</main>
<section>…cookie notice…</section>
<footer>…company links…</footer>5,297 UTF-8 HTML bytes · this page only
# Web context without the chrome
AI agents rarely need the whole interface of a webpage.
They need the useful text, its structure, and enough
source information to explain where the material came from.1,736 UTF-8 Markdown bytes · this page only
For this demo page the Markdown body is shorter than the HTML body (5,297 → 1,736 UTF-8 bytes). That ratio is a property of the fixture, not a product KPI — do not cite it as “Occam saves 67%.” No tokenizer was used; not a token or quality claim.
Method and source revision
Runtime source revision `b3c212c6d9e193619b6e8663148bd53932a0acc0`. Full method, complete input/output, the minimal live smoke proof, controlled failure, and reproduction scripts: [current proof bundle](examples/current-proof/README.md) and three recorded jobs in [golden workflows](examples/golden-workflows/) [context packs](examples/context-packs/), and [site research](examples/site-research/).The cost grows with every source¶
An ordinary page can contain navigation, scripts, repeated interface text, cookie controls, footers, and large amounts of raw markup around the part an agent actually needs.
Passing all of that through wastes a local model's limited context and makes larger models work around irrelevant text. A search result can help find the source; Occam focuses on reading the chosen source and preparing usable page content for the agent.
The measured fixture above makes that transformation inspectable. The proof
bundle also retains example.com as the minimal live smoke case so the richer
marketing example does not replace the smallest deterministic contract check.
A useful result — or an explicit unknown¶
Readable content with the source URL and result metadata.
# Example Domain
This domain is for use in documentation examples…Page content is unknown — do not invent it from memory.
{
"ok": false,
"failure": {
"code": "private_url_blocked",
"message": "Private or local URLs are blocked."
}
}This predictable failure is a trust feature, not the main reason to try Occam: start with the successful read. The proof fixture includes the controlled private-destination case above.
Choose your workflow¶
Three routes. Pick one, then open the matching Quick Start path for the exact prompt.
Connect Cursor, Hermes, or another MCP-capable app, then type the first prompt in a new conversation.
Open AI app paths →Tool-capable local model via Occam’s terminal chat — Ollama is a model runtime, not an MCP host.
Start local Ollama chat →Wire your own MCP client with the generated launch snippet and API contract.
Developer integration →Choose a detailed path and get the exact first prompt · Host onboarding · Workflow gallery · See host validation tiers
How Occam works¶
Occam starts with a lightweight local read and can use a local browser when the page requires it. It then returns the useful content and metadata through one agent-facing contract. Focus, budgets, structured extraction, sessions, and verification are available when the task needs more control.
How Occam works · Read one page · Choose a tool
Why Occam¶
Not “another web fetch.” Occam is the honesty + token-budget layer between your agent and the public web.
| Generic fetch / memory | Occam |
|---|---|
| Empty HTML or invented text | Live Markdown or typed ok:false |
| Burns the context window | Budget + focus prune (deterministic) |
| No proof of what was returned | Optional Receipt v1 → verify |
| One opaque “read” | Ladder, probe, map, search, digest |
Why Occam — full flashcard · Choose a tool · Ask AI / agent prompt
Trust and local control¶
Local-first is not an absolute “never cloud” claim. The origin website is a network source, and explicitly configured search, proxy, or remote transport providers can change the boundary.
Optional Receipt v1 artifacts can check returned-byte integrity against a supplied key. They do not prove truth, identity, or authentic origin.
Trust and security · Capabilities · Reference overview · Installation safety · Receipts
Get your first Occam result¶
Install Occam, choose the path for your AI application or local runtime, and finish with a real page read.
Get your first result Inspect the proof
Explore deeper¶
Why Occam · Task router ·
Workflow gallery · Examples ·
Recipes · Tools ·
Tools reference · MCP API ·
Handbook · Experimental ·
Operators · Troubleshooting ·
FAQ · Reference overview ·
Ask AI · llms.txt
All top-level pages¶
Compact index (gate + scanning). Narrative map: Reference overview.
acquisition · ask-ai · choosing-a-tool · concepts · configuration · datasets · documentation-map · experimental · failure-codes · faq · getting-started · how-occam-works · install · materialization · mcp-hosts · networking · operators · playbooks · quality-baseline · quick-start · receipt_verification · receipts · recipes · roadmap · sessions · tools-reference · transports · troubleshooting · trust-and-safety · what-is-occam · why-occam