What is a context anchor?

It is a short, structured summary of the facts and decisions that must persist across a long conversation. You re-inject it whenever the original history is too long to fit, so the model stays grounded instead of forgetting earlier commitments.

How does the token budget work?

The builder estimates tokens at roughly four characters each and warns you when the anchor exceeds your budget. A tighter budget forces you to keep only the load-bearing facts, which is usually what continuity needs.

Does this replace a real memory system?

No. It is a manual, prompt-level technique for keeping continuity within or across chat sessions. For production apps you'd typically use retrieval or a managed memory layer, but anchoring is a fast, reliable habit for interactive work.

Is anything sent to a server?

No. The anchor is assembled in your browser and the token estimate is computed locally. Nothing is uploaded.

Anchor Context Prompt Builder

Q: Should the anchor go at the top or bottom?

Top placement primes the model before it reads new input and is the common default. Bottom placement keeps the facts freshest right before the model responds, which can help on very long inputs. The builder supports both.

Anchor context prompt builder

Long conversations eventually outgrow the context window — the earliest messages, where the important decisions were made, fall off or get summarized away, and the model starts contradicting things it agreed to earlier. The anchor context prompt builder solves this by generating a compact, structured “anchor” of the conversation’s durable facts and decisions that you re-inject into each new context window. It runs entirely in your browser, no API key.

How it works

You list the key facts and decisions the model must carry forward — constraints, names, choices already made, open questions. You set a token budget and a placement (top or bottom of the new context). The builder then:

Formats your facts into a clearly labeled, easy-to-parse anchor block.
Adds a one-line instruction telling the model to treat the anchor as authoritative ground truth.
Estimates the anchor’s token cost (~4 characters per token) and warns you if it exceeds your budget.
Positions the block according to your placement choice.

Paste the result at the start (or end) of your next message and the model resumes with continuity intact.

Tips and examples

Keep anchors lean — only facts that change the model’s behavior belong there. “We decided to use Postgres, not Mongo,” “the tone is formal,” “the deadline is Friday” are load-bearing; restating an entire discussion is not. A good rule is to cap the anchor at a few hundred tokens so it costs little and stays scannable. Re-generate the anchor whenever a new durable decision is made, and prefer top placement unless your new input is very long, in which case bottom placement keeps the facts freshest right before the model answers.