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Logsift Workflow Research

Error analysis, filtering methodology, and systematic fixing approach for command output.

Research Overview

Date: 2025-12-03 (initial), 2025-12-04 (updated)
Implementation: /logsift and /logsift-auto slash commands
Related: Commit Agent, Context Engineering

Problem Statement

Command Output Overflow

Running installation/test scripts produces massive output:

  • Test script: 10,000+ lines
  • Claude Code context limit: 200k tokens (~30k lines)
  • Single test run: ~50% of context window
  • Multiple runs: Context overflow

Result: Cannot debug iteratively, context fills with success messages

Logsift Solution

What it does: Filters command output to show only errors and warnings

Input: 10,000+ lines of command output
Output: ~200 lines of errors/warnings/key messages
Compression: ~50x reduction

How It Works

logsift monitor -- bash tests/install/test-install.sh

# 1. Runs command in background
# 2. Captures all output
# 3. Shows periodic status updates
# 4. Analyzes when done
# 5. Reports only issues

5-Phase Error Methodology

See Working with Claude Code for the full 5-phase methodology with examples.

Summary:

  1. Initial Analysis — Read the full error report before acting; look for patterns
  2. Root Cause Investigation — Are errors related (shared cause) or independent?
  3. Solution Strategy — Fix root cause if shared; fix independently if not
  4. Iterative Fix-and-Rerun — Re-run same command, compare, repeat until clean
  5. Verification — Confirm solution is robust, not just superficially passing

Two Command Variants

/logsift - Explicit Command

/logsift "bash ~/dotfiles/tests/install/test-install.sh --reuse" 15

Pros:

  • Fast, no interpretation
  • Explicit and unambiguous
  • Claude gets straight to analysis

Cons:

  • Need to know exact path/flags
  • More typing

/logsift-auto - Natural Language

/logsift-auto run wsl docker test with reuse flag, 15 minutes

Pros:

  • Natural language
  • Claude figures out paths
  • Less typing

Cons:

  • Slight interpretation overhead
  • May need clarification

Comparison: Track via metrics to see which works better

Integration with Commit Agent

Commit agent uses logs ift for pre-commit:

# Phase 4: Background (suppress auto-fixes)
pre-commit run > /dev/null 2>&1 || true

# Phase 5: Logsift (show errors only)
logsift monitor -- pre-commit run --files file1.py file2.sh

Token savings: ~950 tokens per pre-commit run

Guiding Principle

Prioritize correctness and root cause fixes over token savings

Logsift already saved massive context by filtering logs. Now use that savings to fix things properly. If thorough investigation requires reading files or exploring code, DO IT.

References

  1. Logsift Tool
  2. URL: https://github.com/user/logsift (project-specific)
  3. Topics: Log filtering, error extraction

Research Date: 2025-12-03, updated 2025-12-04
Status: Production use in slash commands