Transcript Analyzer Skill

Use this skill when you need to analyze Claude Code session transcripts for:

• Debugging plugin behavior
• Understanding context/token usage patterns
• Tracing tool execution flow
• Finding sources of context bloat
• Investigating errors or unexpected behavior

Transcript Location

Claude Code stores session transcripts at:

~/.claude/projects/-PATH-TO-PROJECT/*.jsonl

The path uses dashes instead of slashes. For example:

• Project: /Users/bfreis/dev/myproject
• Transcripts: ~/.claude/projects/-Users-bfreis-dev-myproject/*.jsonl

Transcript Structure

Transcripts use JSONL format (one JSON object per line).

Record Types

Message Structure

{
  "type": "user" | "assistant",
  "uuid": "message-uuid",
  "parentUuid": "parent-message-uuid",
  "sessionId": "session-uuid",
  "isSidechain": false,
  "timestamp": "2025-12-06T...",
  "message": {
    "role": "user" | "assistant",
    "content": [...],
    "usage": { "input_tokens": N, "output_tokens": N }
  }
}

Content Block Types

In assistant messages:

• text - Regular text response
• tool_use - Tool invocation with .id, .name, .input
• thinking - Extended thinking blocks

In user messages:

• text - User input
• tool_result - Tool output with .tool_use_id, .content

Critical Gotchas

1. Content is ALWAYS an array - Even single text blocks
2. Tool result .content can be string OR array - Handle both:

   if .content | type == "array" then
     (.content | map(.text // "") | add)
   else
     .content
   end
   

3. Use []? not [] - Handles missing fields gracefully
4. Sub-agents have isSidechain: true - Filter these for main conversation only
5. parentUuid links threads - Not line order

Using transcript-tool

The skill provides a CLI at scripts/transcript-tool:

# Quick overview
transcript-tool summary session.jsonl

# Find context bloat sources
transcript-tool bloat session.jsonl 15

# Tool usage breakdown
transcript-tool tools session.jsonl

# Trace specific tool
transcript-tool trace-tool session.jsonl Read

# Find errors
transcript-tool errors session.jsonl

# Custom jq query
transcript-tool extract session.jsonl '.type'

Common Analysis Workflows

1. Debug Plugin Behavior

# Find skill invocations
transcript-tool trace-skill session.jsonl plan-generator

# See what tools were used
transcript-tool tools session.jsonl

# Check for errors
transcript-tool errors session.jsonl

2. Investigate Context Bloat

# Find largest tool results
transcript-tool bloat session.jsonl 20

# Message size analysis
transcript-tool messages session.jsonl

# Identify specific large results
transcript-tool extract session.jsonl '
  select(.type == "user") |
  .message.content[]? |
  select(.type == "tool_result") |
  select((.content | tostring | length) > 10000) |
  .tool_use_id
'

3. Trace Execution Flow

# All tool calls in order
transcript-tool extract session.jsonl '
  select(.type == "assistant") |
  .message.content[]? |
  select(.type == "tool_use") |
  "\(.name): \(.input | keys | join(", "))"
'

Raw jq Recipes

For complex analysis, use jq directly:

Count content block types:

jq -r '
  select(.type == "user" or .type == "assistant") |
  .message.content[]? |
  .type
' session.jsonl | sort | uniq -c

Find tool call by ID:

jq -r --arg id "toolu_xxx" '
  select(.type == "assistant") |
  .message.content[]? |
  select(.type == "tool_use" and .id == $id)
' session.jsonl

Get corresponding tool result:

jq -r --arg id "toolu_xxx" '
  select(.type == "user") |
  .message.content[]? |
  select(.type == "tool_result" and .tool_use_id == $id) |
  .content
' session.jsonl

Token usage per message:

jq -r '
  select(.type == "assistant" and .message.usage) |
  "\(.message.usage.input_tokens) in, \(.message.usage.output_tokens) out"
' session.jsonl