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Guide · Agent skill

How to use the Caveman Learn Editor agent skill

Updated · written with AI from the project's own documentation and checked against our catalogue data

The caveman-learn skill is an agent skill for Claude-based coding agents that acts on a report measuring where the agent's tokens go. It reviews the ranked token sinks, proposes concrete cost-lowering fixes, and asks you yes or no before each edit. This guide covers what the skill does, how to install it, how to trigger it, and what it needs before it will work.

Caveman Learn EditorJuliusBrussee/caveman · Apache-2.0

Quick start

  1. 1Install the caveman CLI. Install the caveman command-line tool with its learn and mem subcommands, since the skill cannot run without them.
  2. 2Add the skill. Download the ZIP from this page and unzip it into ~/.claude/skills/, or into a project's .claude/skills/ folder, or upload it under Settings → Capabilities → Skills.
  3. 3Start a new session. Open a fresh agent session so the skill is loaded.
  4. 4Ask in plain language. Request something like lowering your token cost or trimming a heavy CLAUDE.md.
  5. 5Review the report. Let the agent run caveman learn report --json and read the ranked token sinks it shows you.
  6. 6Approve or decline each edit. For each proposed fix, answer yes or no. The agent applies only approved edits and re-measures afterward.

What is an agent skill, and what does caveman-learn make the agent do?

An agent skill is a folder with a SKILL.md file that an agent such as Claude Code loads when a request matches the skill's description. The skill tells the agent how to carry out a specific task.

caveman-learn does not measure anything itself. The caveman learn command measures where tokens go and writes a ranked plan. The skill is the second half: it walks through that plan with you and turns findings into edits, one approved change at a time. After a change it re-measures and reverts the change if tokens per turn did not actually go down.

  • Shows the Cave Score, its four components, and the ranked token sinks (the parts of context that cost the most).
  • Proposes a concrete fix, such as trimming a heavy CLAUDE.md or moving repeated context into cavemem.
  • Asks yes or no before each edit.
  • Re-measures after an edit and reverts it if tokens per turn did not drop.

Install the caveman-learn skill

You can install the skill in one of two ways. The first is to download the ZIP from this page and unzip it into a skills folder. Use ~/.claude/skills/ to make it available to all of your projects, or a project's .claude/skills/ folder to limit it to one repository.

The second is to upload the ZIP in the Claude apps. Open Settings, go to Capabilities, then Skills, and upload the file there.

  • Personal install: unzip into ~/.claude/skills/ so the caveman-learn folder sits inside it.
  • Project install: unzip into the project's .claude/skills/ folder.
  • Claude apps: Settings → Capabilities → Skills, then upload the ZIP.
  • Start a new agent session after installing so the skill is picked up.

Install the caveman CLI before you use the skill

The skill depends on the caveman command-line tool. It calls caveman learn and caveman mem subcommands, and it will not work without them. The source also lists a caveman tools skills install route and a caveman skills install route in the project's documentation; check the README for the form that matches your setup.

Offload fixes also need a cavemem memory store. Without it, the skill can still propose trims to a CLAUDE.md, but it cannot move repeated context into memory.

  • caveman CLI with learn and mem subcommands.
  • cavemem memory store, required only for offload fixes.
  • Agent file tools that can edit CLAUDE.md and write temp files.
caveman learn report --json

Trigger the skill with natural requests

You do not need a special command to use the skill. Ask for what you want in plain language and the agent will load it when the request matches the skill's description. The description names these triggers: asking to lower an agent's token cost, asking what caveman has saved, asking to trim a heavy CLAUDE.md, or asking to offload re-pasted context into cavemem.

  • "Lower my agent's token cost."
  • "What has caveman saved so far?"
  • "My CLAUDE.md is huge. Trim it."
  • "I keep pasting the same context every session. Move it into cavemem."

What a typical session looks like

The agent first runs caveman learn report --json and shows you the findings. It states each sink's class and basis. Behavioral findings are presented as observations with a soft suggestion, not as orders.

For each sink you choose to act on, the agent prepares a candidate with a dry run and shows a before and after figure in tokens per turn. It edits a file only after you say yes, then checks the reduction. If the after figure is not lower than the before figure, it reverts and reports that.

  • Spend figures show what the scanned window cost. They are not what a fix would return, and they are not projected into a month or year.
  • Cache efficiency is a rate used to price other sinks, not a volume of tokens to add up.
  • Session outcomes are correlational. A session without a commit is not automatically a wasted session.
caveman learn apply <sink_id> --dry-run

Safety notes: scripts and network

The skill runs scripts. It also writes files: it edits CLAUDE.md or AGENTS.md when you approve a change, and for offload fixes it writes the block to a temp file and deletes that file once the memory id is returned. Each edit needs your yes.

The skill does not use the network, according to its listing. Memory content is never deleted without your yes. When offloading, the skill passes block text to the memory store through standard input, not on the command line, so shell characters in the text are not interpreted.

  • Runs scripts: yes.
  • Uses network: no.
  • Edits to memory or rules files need your explicit approval for each one.
  • If the source text changed since the scan, the skill aborts that item instead of guessing.

What people use it for

  • Trimming a CLAUDE.md that has grown large and loads every turn.
  • Removing a skill the agent never invokes, after checking the measured cost.
  • Moving a block of context you re-paste each session into cavemem, with a short pointer left in its place.
  • Reviewing a spend summary for a scanned window to see what it cost, labelled as cost for that window only.
  • Finding the same rule loaded from two files and removing the duplicate after you approve.

Frequently asked questions

Is caveman-learn free to use, and what is its licence?

The skill is listed under the Apache-2.0 licence, and the source is public. Check the repository's licence file for the full terms before redistributing it.

Does caveman-learn work without the caveman CLI?

No. The skill depends on the caveman learn and caveman mem commands. Without the CLI installed, the skill will not work.

Will this guarantee I save tokens?

No. The skill itself says spend figures are costs, not returns, and that behavioral findings are correlational. Projected savings can be wrong, so the skill re-measures after each edit and reverts changes that did not reduce tokens per turn.

Does the skill edit my files without asking?

No. It asks yes or no before each edit and never deletes memory content without your approval.

What do I need for cavemem offload fixes?

You need a cavemem memory store. The skill uses it to store a re-pasted block and recall it compactly later, and it keeps the source untouched if recall does not work.

How is this different from just editing CLAUDE.md by hand?

The skill ties edits to measured findings. It shows a before and after figure in tokens per turn, asks for approval on each change, and reverts an edit if the measured reduction is not there. Doing it by hand gives you none of that measurement.

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Our verdict

Use caveman-learn if you run Claude Code with a heavy CLAUDE.md or repeatedly paste the same context, and you already use or are willing to install the caveman CLI. Skip it if you have not installed caveman, or if you expect a guaranteed saving, since the skill itself says its projections can be wrong.

Download the skill