session-search

pchalasani's avatarfrom pchalasani

For CLI agents WITHOUT subagent support (e.g., Codex CLI). Search previous code agent sessions for specific work, decisions, or code patterns.

⭐932stars🔀70forks📁View on GitHub🕐Updated Jan 4, 2026
[Memory and Context Management]

When & Why to Use This Skill

This Claude skill provides a specialized search mechanism for CLI-based AI agents to access and retrieve historical session data. It solves the problem of context fragmentation by allowing agents to query past architectural decisions, code patterns, and specific task implementations, effectively serving as a long-term memory layer that enhances development continuity and consistency.

Use Cases

  • Retrieving Past Design Decisions: Quickly locate historical discussions regarding architectural choices (e.g., choosing JWT over session-based auth) to ensure current work remains aligned with previous logic.
  • Code Pattern Discovery: Search through previous sessions to find and reuse specific implementation patterns or snippets, reducing redundant coding efforts.
  • Contextual Continuity for CLI Agents: Enables agents like Codex CLI to 'remember' work from previous sessions without polluting the current prompt context or exceeding token limits.
  • Project Auditing and Tracking: Audit the evolution of a project by searching for when specific features were implemented or why certain code changes were made in the past.
namesession-search
descriptionFor CLI agents WITHOUT subagent support (e.g., Codex CLI). Search previous code agent sessions for specific work, decisions, or code patterns.

If you are Claude Code: Do NOT use this skill directly. Use the session-searcher subagent via the Task tool instead - it handles this more efficiently without polluting your context.

session-search

Search and find previous code agent sessions (Claude-Code or Codex-CLI) for specific work, decisions, or code patterns.

Workflow

  1. Understand the query: Identify what the user is looking for (code patterns, decisions, specific work, design direction)
  2. Search with aichat: Run aichat search --json -n 10 "[query]" (use -g "project" to filter by project)
  3. Parse results: Use jq to extract fields from JSONL output (session_id, project, created, snippet, file_path)
  4. Deep dive if needed: Read session files at ~/.claude/projects/*/[session-id].jsonl (max 3 files)
  5. Summarize: Return a focused summary with key findings and references

Run aichat search --help to see all options (date filters, branch filters, etc.) and JSONL field names.

Output Format

Return a concise summary containing:

  1. Key Findings: 2-3 bullet points answering the query
  2. Relevant Sessions: Session IDs and dates for reference
  3. Specific Content: Code snippets or quotes if directly relevant

Format as clean markdown, not raw JSON.

Example

Query: "Find sessions where we discussed authentication design"

aichat search --json -n 10 "authentication design"

Summary:

  • Session abc123 (Dec 10): Discussed JWT vs session-based auth, decided on JWT
  • Session def456 (Dec 8): Implemented refresh token rotation pattern

Constraints

  • ALWAYS use --json flag with aichat search (otherwise it spawns interactive UI)
  • NEVER return raw JSON output to the user - summarize and distill findings
  • NEVER read more than 3 session files per query
  • If no results found, suggest alternative search terms
  • ONLY report information directly observed in files - never infer or extrapolate

Error Handling

If aichat search command fails or is not found, ask user to install:

uv tool install claude-code-tools   # Python package
cargo install aichat-search         # Rust search TUI

Prerequisites:

  • Node.js 16+ (for action menus)
  • Rust/Cargo (for aichat-search)

If user doesn't have uv or cargo:

curl -LsSf https://astral.sh/uv/install.sh | sh           # uv
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh  # Rust