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The second brain9 minApplication

Querying a graph rather than rereading everything

A knowledge graph built once answers a question by walking explicit links, which costs noticeably fewer tokens than a full reread of the source files, a gap illustrated by a public example that carries its own caveat, and the same principle applies to an old session transcript, queried by levels before being reopened in full.

A knowledge graph links the elements of a project, files, functions, notes, through explicit links rather than through their mere position in a folder, and answering a question by walking these links costs noticeably less than a full reread of the source files. Graphify, a third-party tool built for assistants such as Claude, Cursor or Codex, applies this principle to a project's code: it is not an Anthropic feature, but a separate piece of software that builds its own graph once, then answers questions by querying it rather than rereading every file.

A figure, with its own caveat

The most concrete public example comes from Graphify's own blog: a community user reports there having consumed roughly seventy-one point five times fewer tokens by querying their project's graph rather than directly rereading the whole set of their source files for the same question.

The article that publishes it describes it itself as a figure relayed by the community rather than a benchmark result, with no published method that would allow it to be reproduced identically on another project, and with no absolute token value attached. Retaining the principle, a queried graph costs less than a full reread, matters more than retaining a precise factor calculated from a single testimonial.

A stale graph answers wrong

A graph built once can be frozen, partial, and silent about the links between your notes, with nothing to say so: a query then returns a wrong result with confidence. Compare the graph's date with that of the files before each query, and rebuild it if it is older. A word or a proper name is found by a text search, a relation between two elements by the graph.

The same principle for an old session transcript

The logic extends to another type of heavy file, the transcript of a long past work session. Rather than reopening a whole transcript every time a question concerns an old decision, a three-level method limits the reading to what is strictly necessary:

level 1: read the summary reminder, a few lines
if the answer is enough, stop here
level 2: grep the relevant passage in the transcript, read only the targeted portion
if the answer is enough, stop here
level 3: read the whole transcript, only if the previous two levels still leave doubt

Reading the whole transcript stays reserved for the last level, when the note seems out of date or the answer looks doubtful. You build this method yourself, like nightly memory consolidation, which can rely on an already refreshed graph rather than rereading everything each night.

Figure 1

A public example, with its own caveat

71.5times fewer tokens
reported by a Graphify community user when querying their project's graph rather than rereading the whole set of their source files
graphify.com, blog, 2026-07-13
Graphify, a third-party knowledge-graph tool for code and not an Anthropic product, itself describes this report as a figure relayed by the community rather than a rigorous measurement: it stands as an example, not as a reference to reproduce as is.
Calibrate it yourself

A cooperative's coordinator queries a knowledge graph built on the code of a small internal project and notes the token consumption shown at the end of the answer. She then asks Claude the same question, telling it to directly reread the entire set of source files for the same project, and notes the token consumption shown at the end of this second answer: the graph consumed noticeably less.

Write in one sentence what this situation establishes, and in one sentence what it does not establish.

What to remember
  • A knowledge graph links the elements of a project through explicit links and answers a question by walking these links rather than rereading every file in full.
  • Graphify is a third-party knowledge-graph tool for code, built for assistants such as Claude, and not a feature built in by Anthropic.
  • The most concrete publicly available figure is itself described by its own source as a figure relayed by the community, not the result of a rigorous benchmark.
  • The same logic applies to an old session transcript: query a summary reminder first, then a targeted portion, and only drop down to a full read if the answer is missing or looks out of date.
  • A graph built once can be stale or partial without saying so: its date is compared with the files' before each query, and a proper name is found by text search.
Do this now

Pick a code or notes folder you consult often, ask Claude a precise question about it, and note whether the answer relies on an already built summary or on a full reread of the files, before judging whether a graph or an index would save you time.

What still needs checking

These points depend on an interface or a rule that may have changed since this was written. Check them on your own screen before relying on them.

  • If you install Graphify yourself, check on its own blog page whether this figure has been updated or refined since: it can change without the underlying measurement itself having changed.
Check the source

Every datable claim in this lesson links here to the public text behind it. A source that does not open proves nothing.