prompt-logExtract conversation transcripts from AI coding session logs (Clawdbot, Claude Code, Codex). Use when asked to export prompt history, session logs, or transcripts from .jsonl session files.
Install via ClawdBot CLI:
clawdbot install thesash/prompt-logRun the bundled script on a session file:
scripts/extract.sh <session-file>.jsonl session log from Clawdbot, Claude Code, or Codex.--after and --before ISO timestamps.--output path for the markdown transcript..prompt-log/YYYY-MM-DD-HHMMSS.md in the current project.scripts/extract.sh ~/.codex/sessions/2026/01/12/abcdef.jsonl
scripts/extract.sh ~/.claude/projects/my-proj/xyz.jsonl --after "2026-01-12T10:00:00" --before "2026-01-12T12:00:00"
scripts/extract.sh ~/.clawdbot/agents/main/sessions/123.jsonl --output my-transcript.mdjq in PATH.gdate if available on macOS; otherwise falls back to date.Generated Mar 1, 2026
Development teams use the prompt log to analyze AI coding session transcripts during sprint retrospectives. They review how AI assistants were prompted, identify patterns in successful interactions, and improve team prompting strategies for better productivity.
AI research labs extract conversation transcripts from coding sessions to build training datasets for fine-tuning coding assistants. They filter sessions by timestamp to collect specific types of interactions and export them in standardized markdown format for annotation pipelines.
Engineering managers analyze prompt logs to measure how their teams interact with AI coding tools. They extract transcripts from multiple sessions, filter by time periods to track weekly/monthly usage patterns, and generate reports to optimize AI tool adoption across the organization.
Coding bootcamps and computer science instructors use the tool to export student-AI interaction transcripts from practice sessions. They review how students formulate prompts, identify common misunderstandings, and provide targeted feedback on effective AI communication techniques.
Compliance teams in regulated industries extract and archive AI coding session transcripts for audit trails. They use timestamp filters to isolate sessions from specific periods and maintain organized markdown records of all AI-assisted development activities.
Offer the prompt log extraction tool as part of a premium developer productivity suite. Charge monthly subscriptions for teams needing regular session analysis, with tiered pricing based on the number of developers and advanced filtering features.
Integrate the transcript extraction capability into a larger AI governance platform for enterprises. Sell annual licenses to companies needing compliance, security, and productivity monitoring for their AI coding tool usage across development teams.
Use the tool to collect and process AI coding session transcripts, then sell curated datasets to AI companies for model training. Offer different dataset packages filtered by programming language, task type, or interaction patterns with premium pricing for specialized collections.
💬 Integration Tip
Install jq dependency during setup and ensure proper date command compatibility across operating systems. Consider adding the extraction script to project CI/CD pipelines for automated transcript generation.
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