agentleFS
Piebald-AIPiebald-AI/splitrail/AGENTS.md

splitrail

AGENTS.md228 starsChanged 5 months agoMITView on GitHub

Splitrail is a high-performance, cross-platform usage tracker for AI coding assistants (Claude Code, Copilot, Cline, Pi Agent, etc.). It analyzes local data files from these tools, aggregates usage statistics, and provides real-time TUI monitoring with optional cloud upload capabilities. Pluggable architecture with the Analyzer trait. Registry in src/analyzer.rs, individual analyzers in src/analyzers/. Each analyzer discovers data sources, parses conversations, and normalizes to a common format. Run after code changes: Skills provide task-specific guidance. Use the skill tool to load one…

  • Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.

    Of the AGENTS.md files we read, the 31,700 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.

  • In this repository7 other files it gives its agents.

The file

We split this AGENTS.md into the rules it gives an agent

5 rules. About 0 are common, 2 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Follow Rust 2024 edition conventions

    line 21
  2. Very specific:

    Use anyhow::Result for error handling

    line 22
  3. Very specific:

    Prefer async/await over raw futures

    line 23
  4. Very specific:

    Use parking_lot locks over std::sync for performance

    line 24
  5. Distinctive:

    Run after code changes:

    line 28

≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
AGENTS.md

Project Overview

Splitrail is a high-performance, cross-platform usage tracker for AI coding assistants (Claude Code, Copilot, Cline, Pi Agent, etc.). It analyzes local data files from these tools, aggregates usage statistics, and provides real-time TUI monitoring with optional cloud upload capabilities.

Architecture

Analyzer System

Pluggable architecture with the Analyzer trait. Registry in src/analyzer.rs, individual analyzers in src/analyzers/. Each analyzer discovers data sources, parses conversations, and normalizes to a common format.

Data Flow

  1. Discovery: Analyzers find data files using platform-specific paths (src/analyzers/)
  2. Parsing: Parse JSON/JSONL into normalized messages (src/types.rs)
  3. Deduplication: Hash-based dedup using global hash field
  4. Aggregation: Group by date, compute token counts, costs, file ops (src/utils.rs)
  5. Display: TUI renders daily stats + real-time updates (src/tui.rs, src/watcher.rs)

Code Style

  • Follow Rust 2024 edition conventions
  • Use anyhow::Result for error handling
  • Prefer async/await over raw futures
  • Use parking_lot locks over std::sync for performance

Post-Change Verification

Run after code changes:

cargo build --quiet
cargo test --quiet
cargo clippy --quiet -- -D warnings
cargo doc --quiet
cargo fmt --all --quiet

Additional Context

Skills provide task-specific guidance. Use the skill tool to load one when needed - available skills are listed in its description.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.