Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/0p9b/TLDRWrote 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/commands/0p9b/tldr/tldr-compress)<a href="https://agentmods.dev/commands/0p9b/tldr/tldr-compress"><img src="https://agentmods.dev/badge/commands/0p9b/tldr/tldr-compress.svg" alt="Measured on agentmods" 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 | $0.00012 | $0.00081 |
| Opus 5 | $0.00006 | $0.00041 |
| Sonnet 5 | $0.00002 | $0.00016 |
| Haiku 4.5 | $0.00001 | $0.00008 |
Grade A, and why
tldr-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.
What it actually says
Compress the file: $ARGUMENTS.
First check if file is text/prose (.md, .txt). If code, skip. Keep structure, code, URLs, paths, and identifiers. Drop articles, filler, pleasantries, hedging. Save backup to FILE.original.md, overwrite original with compressed.
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 · 10 lines · 12 tokens per session scan A 40b2804d6269
tldr-compress is a command published in the GitHub repository 0p9b/TLDR (23 stars, last pushed 15d ago), licensed MIT. It adds 12 tokens to every session and 81 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
output
Generate output artifacts from active wiki content — summaries, reports, study guides, slide outlines, timelines, glossaries, comparisons. Outputs are filed back into the wiki.
hep-graph.body
A command for viewing saved Agentlas automation graphs and requesting that one be run. The desktop app performs the actual run.
eg-fix-bug
Fix a bug using the elephant/goldfish workflow — problem doc, goldfish diagnosis check, failing test, fix, review, validate.
gpd:update
Update GPD to latest version with changelog display.
reflect-skills
Run the local claude-reflect skill-discovery fallback and propose skill/rule changes without applying them.
checklist
Generate a custom checklist for the current feature based on user requirements.