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.
npx agentmods add instructions/launch-it-labs/log-reducer/agents-mdgit clone --depth 1 https://github.com/launch-it-labs/log-reducerWhat 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 | $0.00496 | $0.00496 |
| Opus 5 | $0.00248 | $0.00248 |
| Sonnet 5 | $0.00099 | $0.00099 |
| Haiku 4.5 | $0.00050 | $0.00050 |
Grade A, and why
log-reducer AGENTS.md 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Log Reducer — Agent Instructions
This repository contains a log reduction tool that compresses verbose log output for AI consumption, achieving 50-90% token reduction while preserving semantic value.
Available tool
CLI (works with any agent that can execute shell commands):
node out/src/cli.js < input.log
Or pipe from another command:
some-command 2>&1 | node out/src/cli.js
The CLI reads log text from stdin and writes the reduced version to stdout.
When to reduce logs
Use the log reducer before inserting log content into a conversation whenever:
- The log is longer than ~50 lines
- The log contains UUIDs, tokens, or long hex strings
- The log has repeated/duplicated lines
- The log contains stack traces with framework internals
What it does
The pipeline applies 11 transforms in order:
- Strip ANSI escape codes
- Normalize whitespace (collapse blank lines, trim trailing spaces)
- Shorten IDs (UUIDs, hex strings, JWT tokens, generated IDs →
$1,$2, ...) - Shorten URLs (strip query params, collapse long paths)
- Simplify timestamps
- Filter noise (health checks, heartbeats, devtools artifacts)
- Strip source locations (browser console
file.js:lineprefixes) - Compress shared prefixes (factor out repeated date/module/time prefixes)
- Deduplicate consecutive identical/near-identical lines
- Detect repeating multi-line cycles
- Fold stack traces (collapse framework internals, shorten file paths)
Project structure
src/pipeline.ts—minify(input: string): string— the main entry pointsrc/transforms/— Individual transform modulessrc/cli.ts— CLI stdin/stdout wrappersrc/mcp-server.ts— MCP server for Claude Codetest/fixtures/— Test fixtures (input.log + expected.log pairs)
Building
npm install
npx tsc -p ./
Testing
npm test
For Claude Code users
This project includes an MCP server configuration in .mcp.json (project root) that automatically exposes a reduce_log tool. See .claude/CLAUDE.md for details.
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.
- 2d ago First seen · 70 lines · 496 tokens per session scan A dd6e949eccbb
log-reducer AGENTS.md is an instructions file published in the GitHub repository launch-it-labs/log-reducer (0 stars, last pushed 5mo ago), licensed MIT. It adds 496 tokens to every session, about $0.0025 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 2026-08-31.
Other instructions, from other repositories
autotask-mcp dev_workflow.instructions.md
Guide for using Taskmaster to manage task-driven development workflows.
ai-workflow AGENTS.md
Instructions for cunhaax/ai-workflow, covering ai workflow template, rules — non-negotiable, project overview, commands and architecture.
trackly-cli CLAUDE.md
Claude Code instructions for trackly-app/trackly-cli, covering trackly-cli, tech stack, backend production source of truth, directory structure and key commands.
foggy-data-mcp-bridge-python CLAUDE.md
Instructions for foggy-projects/foggy-data-mcp-bridge-python, covering foggy data mcp bridge — python, 快速启动, 安装依赖, 运行测试 and 启动 mcp 服务(连接 docker mysql).
McpServer AGENTS.md
AGENTS.md instructions for sharpninja/McpServer, covering agent instructions, session start, rules, byrd test gate and where things live.
AmbyKit CLAUDE.md
Instructions for ambystechcom/AmbyKit, covering claude code — notes for the ambykit repo and claude-specific.