Agent-Skills.md

Agent Skills: Déglacer — CC Session JSONL Reference

>

UncategorizedID: spm1001/claude-suite/deglacer

Repository

spm1001/claude-suite
spm1001License: MIT
3

Install this agent skill to your local

pnpm dlx add-skill https://github.com/spm1001/trousse/tree/HEAD/skills/deglacer

Skill Files

Browse the full folder contents for deglacer.

Download Skill

Loading file tree…

skills/deglacer/SKILL.md

Skill Metadata

Name
deglacer
Description
>

Déglacer — CC Session JSONL Reference

Deglazing the pan to lift the fond — extracting the good bits from past sessions.

When to Use This Skill

You are working with Claude Code session data. This includes:

  • Introspecting past conversations — "what did we discuss last session?", "when did we first talk about X?"
  • Searching session history — finding sessions that mention a topic, tool, or file
  • Parsing JSONL transcripts — extracting human messages, tool calls, thinking blocks, token usage
  • Building tooling — anything that reads ~/.claude/projects/ session data
  • Debugging session format — understanding why a jq query returns nothing

Do NOT guess at the schema. The CC JSONL format has multiple entry types, triple-duty user entries, streaming-duplicated message.ids, and inconsistent field presence across versions. This reference is the source of truth.

When NOT to Use

  • Git history — use git log / git blame for code change history
  • Current conversation state — you already have context, no need to parse your own session
  • Non-CC JSONL files — this schema is specific to Claude Code sessions

deglacer — The CLI Tool

deglacer is the CC JSONL extraction CLI, installed as a uv tool. Use it instead of raw jq for structured extraction.

# Install (once) — from the source repo (local clone, else git+https):
uv tool install 'deglacer @ git+https://github.com/spm1001/deglacer'

# Use:
deglacer SESSION.jsonl

Commands

deglacer SESSION.jsonl                  # conversation text (human + assistant)
deglacer --summary SESSION.jsonl        # human messages only (what was discussed)
deglacer --with-tools SESSION.jsonl     # include tool call summaries
deglacer --with-thinking SESSION.jsonl  # include thinking blocks
deglacer --last 5 SESSION.jsonl         # last 5 turns only
deglacer --json SESSION.jsonl           # structured JSON output
deglacer --stats SESSION.jsonl          # session statistics (tokens, models, tools)
deglacer --timeline SESSION.jsonl       # timestamped turn log
deglacer --find "search term"           # search across recent sessions
deglacer --recent                       # list recent sessions (default 20)
deglacer --recent 10                    # list N most recent
deglacer --today                        # list today's sessions
deglacer --since 2026-03-25             # sessions since a date

Combining Flags

deglacer --with-tools --last 10 SESSION.jsonl    # recent turns with tools
deglacer --with-tools --with-thinking --json ...  # everything, structured
deglacer --summary --last 5 SESSION.jsonl         # quick recap of recent turns

File Discovery

Sessions live at:

~/.claude/projects/{encoded-cwd}/{session-uuid}.jsonl

Where {encoded-cwd} replaces / with - in the project path. Subagent transcripts: {session-uuid}/subagents/agent-{id}.jsonl.

Find recent sessions:

ls -lt ~/.claude/projects/*/*.jsonl | head -20

Find sessions for a project:

ls -lt ~/.claude/projects/-home-modha-Repos-myproject/*.jsonl

Match session to slug/name:

head -1 SESSION.jsonl | jq '{sessionId, slug, version}'

The Schema

Each line in a .jsonl file is one JSON object. The .type field discriminates.

Entry Types

| Type | Purpose | Has timestamp? | |------|---------|---------------| | assistant | Claude's response | Yes | | user | Human msg / tool result / skill injection | Yes | | progress | Streaming bash/hook/agent output | Yes | | system | Turn timing, API errors, slash commands | Yes | | summary | Context compaction | No | | queue-operation | Input typed while Claude busy | Yes | | last-prompt | Records last user text | No | | custom-title | User-set session name | No | | agent-name | Session agent name | No | | file-history-snapshot | File backup state | No | | pr-link | Created PR reference | Yes | | saved_hook_context | Persisted hook output | Yes |

Common Fields (on user/assistant entries)

uuid            string    Unique entry ID
parentUuid      string?   Previous entry (linked list)
sessionId       string    Session UUID (matches filename)
timestamp       string    ISO 8601
cwd             string    Working directory
gitBranch       string    Current git branch
version         string    CC version (e.g. "2.1.85")
slug            string    Human-readable session name
userType        string    Always "external"
entrypoint      string    "cli" (absent in v2.0.x)
isSidechain     boolean   Side conversation flag

assistant entries

{
  "type": "assistant",
  "message": {
    "id": "msg_...",
    "type": "message",
    "role": "assistant",
    "model": "claude-opus-4-6",
    "content": [/* content blocks */],
    "stop_reason": "end_turn" | "tool_use" | null,
    "usage": {
      "input_tokens": 119,
      "cache_creation_input_tokens": 18531,
      "cache_read_input_tokens": 36004,
      "output_tokens": 500
    }
  },
  "requestId": "req_..."
}

Content block types:

  • {type: "text", text: "..."} — Claude's text
  • {type: "tool_use", id: "toolu_...", name: "Bash", input: {...}} — tool call
  • {type: "thinking", thinking: "...", signature: "..."} — extended thinking

DRAGON: Multiple entries share the same message.id. CC streams incremental updates. Merge content blocks by message.id, dedup tool_use blocks by their id field. deglacer handles this automatically.

DRAGON: stop_reason is null in older sessions (pre-v2.1.79).

user entries (TRIPLE DUTY)

The user type serves three purposes. Discriminate with:

| Subtype | How to detect | Content shape | |---------|--------------|---------------| | Human message | typeof content === "string", has permissionMode | String | | Tool result | Has toolUseResult | Array of {type: "tool_result"} | | Skill/system injection | isMeta: true | Array of {type: "text"} |

Human message:

{
  "type": "user",
  "message": {"role": "user", "content": "the actual human text"},
  "permissionMode": "default",
  "promptId": "..."
}

Tool result:

{
  "type": "user",
  "message": {"role": "user", "content": [
    {"type": "tool_result", "tool_use_id": "toolu_...", "content": "output text"}
  ]},
  "toolUseResult": {/* shape varies by tool */},
  "sourceToolAssistantUUID": "..."
}

toolUseResult shapes:

| Tool | Keys | |------|------| | Bash | stdout, stderr, interrupted, isImage, noOutputExpected | | Bash (large) | + persistedOutputPath, persistedOutputSize | | Write/Edit | content, filePath, originalFile, structuredPatch, type | | Read | file, type | | Agent | agentId, agentType, content, prompt, status, totalDurationMs, totalTokens, totalToolUseCount, usage | | Error | Bare string: "User rejected tool use" |

Token Counting

The input_tokens field is ONLY the non-cached portion. Real input = input_tokens + cache_creation_input_tokens + cache_read_input_tokens.

summary entries (minimal)

{"type": "summary", "leafUuid": "...", "summary": "short text"}

No uuid, parentUuid, timestamp, version, or sessionId. Three fields only.

system entries

.subtype discriminates:

  • turn_duration: {durationMs, messageCount}
  • api_error: {error: {status, headers, requestID}, retryInMs, retryAttempt}
  • local_command: {content: "...", level: "info"} — slash commands

jq Recipes (when deglacer isn't enough)

Quick schema discovery (do this FIRST, not head | jq .):

jq -r '.type' FILE.jsonl | sort | uniq -c | sort -rn

Extract human messages:

jq -r 'select(.type == "user" and .permissionMode and (.isMeta | not))
  | .message.content' FILE.jsonl

Extract assistant text (handles multi-block):

jq -r 'select(.type == "assistant")
  | [.message.content[]? | select(.type == "text") | .text]
  | select(length > 0) | join("\n")' FILE.jsonl

Extract tool calls:

jq -c 'select(.type == "assistant")
  | [.message.content[]? | select(.type == "tool_use")
  | {tool: .name, input_keys: (.input | keys)}]
  | select(length > 0)' FILE.jsonl

Session timeline:

jq -c 'select(.type == "user" or .type == "assistant")
  | {ts: .timestamp, type, model: .message.model?}' FILE.jsonl

Token usage per turn:

jq -c 'select(.type == "assistant") | .message.usage
  | {in: (.input_tokens + .cache_creation_input_tokens + .cache_read_input_tokens),
     out: .output_tokens}' FILE.jsonl

Find sessions mentioning a term:

# Prefer: deglacer --find "term"
# Raw jq fallback:
for f in ~/.claude/projects/*/*.jsonl; do
  if jq -e 'select(.type == "user" and (.message.content | type) == "string"
    and (.message.content | test("term"; "i")))' "$f" >/dev/null 2>&1; then
    echo "$f"
  fi
done

Anti-Patterns (DON'T)

| Don't | Why | Do instead | |-------|-----|-----------| | jq -s '.' on JSONL | Slurps entire file into memory as array | Stream line-by-line (default jq behaviour) | | jq '.[]' on JSONL | JSONL isn't an array | Each line is already a separate object | | .role at top level | Role is at .message.role, not top-level | Use .type for entry type | | .type == "message" | No such type | Types: user, assistant, progress, system, etc. | | .type == "human" | No such type | .type == "user" + check it's not a tool result | | head -1 \| jq . for discovery | Wastes a turn, first line may be queue-operation | jq -r '.type' \| sort \| uniq -c | | Assume content is string | Assistant content is always array; user content varies | Check type before accessing | | 2>/dev/null on everything | Hides real errors | Understand the schema, don't hedge | | Guess at field names | 39% of jq-on-.claude commands are schema discovery | Read this reference |