Session extract
Agent-facing primitive. Extract filtered content from a single Claude Code, Codex, or Cursor session file — either a conversation skeleton or error signals.
This skill exists so that agents do not read multi-megabyte session files into context. The scripts under
own the JSONL shape knowledge and emit a narrative-readable digest.
Arguments
Space-separated positional args:
- — absolute path to a session JSONL file (typically a value returned by ).
- — or .
- (optional) — or to cap output at N lines (e.g., ). Omit to return full extraction.
Execution
Skeleton mode — narrative of user messages, assistant text, and collapsed tool-call summaries:
bash
cat <file> | python3 scripts/extract-skeleton.py
Errors mode — just error signals:
bash
cat <file> | python3 scripts/extract-errors.py
If
is
, pipe through
. If
, pipe through
. Apply the limit after the Python script, never before — the
line is emitted last and a head cap may drop it; that is acceptable when the caller asks for a head cap.
Return the raw stdout verbatim. Do not paraphrase, annotate, or synthesize — the caller does synthesis across multiple sessions.
What each mode returns
Skeleton
Narrative output with one logical event per block, separated by
:
- User messages (text only, no tool results, framework wrapper tags stripped)
- Assistant text (no thinking/reasoning blocks — those are internal or encrypted)
- Tool call summaries; 3+ consecutive same-name calls are collapsed (e.g.,
[tools] 5x Read (file1, file2, +3 more) -> all ok
)
Ends with a
line:
{"_meta": true, "lines": N, "parse_errors": N, "user": N, "assistant": N, "tool": N}
.
Errors
One line per error, separated by
:
- Claude Code: tool results with
- Codex: events with non-zero exit or non-empty stderr
- Cursor: always empty — Cursor agent transcripts do not log tool results
Ends with a
line:
{"_meta": true, "lines": N, "parse_errors": N, "errors_found": N}
.
Error handling
If the file cannot be read, let the error surface to the caller. If
reports
, return the output as-is — partial extraction is still useful and the caller decides whether to widen the search or deep-dive further.