Borrowing it
Nothing to install: this file belongs to abhinavteja123/codemore. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/abhinavteja123/codemore/main/.agents/skills/caveman-compress/SKILL.mdgit clone --depth 1 https://github.com/abhinavteja123/codemoreWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/abhinavteja123/codemore/caveman-compress)<a href="https://agentmods.dev/skills/abhinavteja123/codemore/caveman-compress"><img src="https://agentmods.dev/badge/skills/abhinavteja123/codemore/caveman-compress/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/abhinavteja123/codemore/caveman-compress"><img src="https://agentmods.dev/badge/skills/abhinavteja123/codemore/caveman-compress.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00077 | $0.01063 |
| Opus 5 | $0.00039 | $0.00531 |
| Sonnet 5 | $0.00015 | $0.00213 |
| Haiku 4.5 | $0.00008 | $0.00106 |
Grade A, and why
caveman-compress scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to caveman-compress — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Caveman Compress
Purpose
Compress natural language files (CLAUDE.md, todos, preferences) into caveman-speak to reduce input tokens. Compressed version overwrites original. Human-readable backup saved as <filename>.original.md.
Trigger
/caveman-compress <filepath> or when user asks to compress a memory file.
Process
-
The compression scripts live in
scripts/(adjacent to this SKILL.md). If the path is not immediately available, search forscripts/__main__.pynext to this SKILL.md. -
From the directory containing this SKILL.md, run:
python3 -m scripts <absolute_filepath>
- The CLI will:
- detect file type (no tokens)
- call Claude to compress
- validate output (no tokens)
- if errors: cherry-pick fix with Claude (targeted fixes only, no recompression)
- retry up to 2 times
- if still failing after 2 retries: report error to user, leave original file untouched
- Return result to user
Compression Rules
Remove
- Articles: a, an, the
- Filler: just, really, basically, actually, simply, essentially, generally
- Pleasantries: "sure", "certainly", "of course", "happy to", "I'd recommend"
- Hedging: "it might be worth", "you could consider", "it would be good to"
- Redundant phrasing: "in order to" → "to", "make sure to" → "ensure", "the reason is because" → "because"
- Connective fluff: "however", "furthermore", "additionally", "in addition"
Preserve EXACTLY (never modify)
- Code blocks (fenced ``` and indented)
- Inline code (
backtick content) - URLs and links (full URLs, markdown links)
- File paths (
/src/components/...,./config.yaml) - Commands (
npm install,git commit,docker build) - Technical terms (library names, API names, protocols, algorithms)
- Proper nouns (project names, people, companies)
- Dates, version numbers, numeric values
- Environment variables (
$HOME,NODE_ENV)
Preserve Structure
- All markdown headings (keep exact heading text, compress body below)
- Bullet point hierarchy (keep nesting level)
- Numbered lists (keep numbering)
- Tables (compress cell text, keep structure)
- Frontmatter/YAML headers in markdown files
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 112 lines · 77 tokens per session scan A 8b0d64c622d8
caveman-compress is a skill published in the GitHub repository abhinavteja123/codemore (2 stars, last pushed 1mo ago), licensed MIT. It adds 77 tokens to every session and 1,063 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to caveman-compress, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
docs-refresh
Full documentation hygiene pass: memory, CLAUDE.md, lessons, references, guides. Audit freshness, delete stale, update outdated, compress index.
trajectory
Internal dynos-work skill. Sequence memory manager. Stores compact task traces and retrieves similar prior tasks to inform discovery and design review. Runs only when the user explicitly types /dynos-work:trajectory; never auto-triggered from conversation.
anchor.write
A tool for adding Anchorlaw labels to public functions: test claims backed by runtime evidence, or explicit statements about what is still unknown.
compound-memory
Extract session patterns via transcript analysis to project memory.
ai-debt-audit
Scan a repository for AI-generated technical, cognitive, and intent debt. Use when the user asks to audit a codebase for AI/vibe-coding risk, check for issues an AI coding assistant may have introduced (disabled RLS, hardcoded secrets, missing auth checks, SSTI, debug mode left on), assess technical debt after heavy…
half-clone
Clone later half of conversation, discarding earlier context.