Skip to main content

cc-transcript

Grep every Claude Code session you've ever run. The lossless Rust parser reads Claude Code's on-disk JSONL at 169 MB/s; the compiled CLI greps it and renders one line per event, 25 ms cold.

CI PyPI License PolyForm Noncommercial

Get started

uvx cc-transcript list

Every session is already on disk under ~/.claude/projects. list finds them newest first, and stats collapses one into a screenful:

Terminal running 'uvx cc-transcript stats' — one session summarized as counts, kinds, models, and tool names

Driving with an agent? Paste this:

/plugin marketplace add yasyf/cc-transcript
/plugin install cc-transcript@cc-transcript

The plugin's skill teaches Claude to answer "what did I ask you yesterday" from its own history, funneling through the CLI instead of reading raw JSONL.

No Claude Code? Point any agent at the CLI
Use `uvx cc-transcript` to investigate my Claude Code sessions: `list` finds
transcripts on disk, `stats` summarizes one, `grep` searches content, and `show`
renders one compact line per event. Start by listing my newest sessions and
summarizing the most recent one. Docs: https://yasyf.github.io/cc-transcript/

Use cases

Ask Claude what you asked Claude yesterday

Yesterday's session is a megabyte of JSONL, and pasting it into a chat blows the context window. Render the spine instead:

uvx cc-transcript show --signal --tail 20 ~/.claude/projects/<project>/<session>.jsonl

--signal keeps only the substantive user and assistant turns. One line per event, a few hundred tokens for the whole exchange. With the plugin installed, skip the command and ask Claude directly; its skill runs this funnel for you.

Find the session where you fixed that bug

The fix happened weeks ago, in one of a few hundred transcripts. Search them all:

uvx cc-transcript grep "TranscriptExpiredError" --project cc-transcript

Hits print under their transcript's path, each line carrying its raw event index; feed an index back into show --range to re-read the conversation around the fix. grep searches your newest 50 transcripts by default; --all takes it to every session on disk, and a no-match run exits 1 so it scripts cleanly.

Debug a token blowup from transcript evidence

A session burned through the context window and you want the culprit, not a guess. Rank the evidence:

uvx cc-transcript stats --per-file --project myapp

Each block reports text, thinking, and tool-io bytes plus per-tool call counts; the blowup stands out as an outsized tool io line. Then grep --tool <name> --with-result pins it to the exact calls.

Script it from Python

The CLI's funnel is four commands; your own tooling wants the events themselves. parse turns a path into a Transcript of typed lazy views, with the noise already dropped inside the engine:

from cc_transcript import NOISE_SPEC, discover, parse

transcript = parse(discover()[0], drop=NOISE_SPEC)
print(len(transcript.events), "events after the noise drop")

discover() lists every transcript on disk newest first, stream fans a whole corpus across the parse pool, and resolve finds one session by UUID. parse also reads OpenAI Codex CLI rollouts — hand it a path from ~/.codex/sessions and the same typed events come back. The getting-started guide builds this out to a composed filter and a sentiment score.

JSON output schema

show --json and grep --json emit JSONL, with one object per event. Each event uses the envelope {i, kind, meta, model, text, blocks, stop_reason, usage}; fields that do not apply to its kind are omitted. Every object in blocks has a type discriminator such as text, thinking, tool_use, tool_result, or fallback.

More in the docs

  • The Python library turns a transcript into typed lazy views, a composed filter, and a score in a dozen lines.
  • Filtering events covers composable clauses, specs, and the ready-made NOISE_SPEC.
  • Sentiment scoring buckets conversations and scores them around any inference engine.
  • Feedback mining runs detectors, confidence calibration, and LLM verdict passes over your corpus.
  • The Rust engine is the implementation — parsing, filtering, scoring, and mining — its correctness pinned by hand-owned literals and golden fixtures.
  • Codex rollouts make the parser two-provider: OpenAI Codex CLI sessions lower into the same typed events, with rollout discovery, subagent joins, and per-session lifecycle and token totals. list --provider codex finds them from the shell.
  • API reference documents the complete typed surface, from TranscriptEvent to SessionActivity.

Read the docs for the full guide. Licensed under PolyForm Noncommercial 1.0.0.

Metadata

Release files for cc-transcript 14.46.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for cc-transcript 14.46.7
File Size Uploaded Provenance Actions
cc_transcript-14.46.7.tar.gz 12.9 MB With provenance Details for cc_transcript-14.46.7.tar.gz

Built distributions (wheels)

Table of built distributions (wheels) for cc-transcript 14.46.7
File Actions
cc_transcript-14.46.7-cp313-abi3-manylinux_2_28_x86_64.whl CPython 3.13 abi3 Linux glibc 2.28+ x86-64 Details for cc_transcript-14.46.7-cp313-abi3-manylinux_2_28_x86_64.whl
cc_transcript-14.46.7-cp313-abi3-manylinux_2_28_aarch64.whl CPython 3.13 abi3 Linux glibc 2.28+ ARM64 Details for cc_transcript-14.46.7-cp313-abi3-manylinux_2_28_aarch64.whl
cc_transcript-14.46.7-cp313-abi3-macosx_11_0_x86_64.whl CPython 3.13 abi3 macOS 11.0+ x86-64 Details for cc_transcript-14.46.7-cp313-abi3-macosx_11_0_x86_64.whl
cc_transcript-14.46.7-cp313-abi3-macosx_11_0_arm64.whl CPython 3.13 abi3 macOS 11.0+ ARM64 Details for cc_transcript-14.46.7-cp313-abi3-macosx_11_0_arm64.whl

Total release size: 110.1 MB

Release files / cc_transcript-14.46.7.tar.gz

Download URL cc_transcript-14.46.7.tar.gz
Size 12.9 MB
Tags Source
SHA-256 checksum
How to use checksums
7ab95d45050422f85c25737d92734595259912b60f226eae12f5db9cb74529c7
BLAKE2b-256 checksum
How to use checksums
40b27e750cca8955cca5eb16264af5a7b45bb12cd946babfe376959569e31349
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 3, 2026.

Transparency log

Release files / cc_transcript-14.46.7-cp313-abi3-manylinux_2_28_x86_64.whl

Download URL cc_transcript-14.46.7-cp313-abi3-manylinux_2_28_x86_64.whl
Size 25.0 MB
Tags CPython 3.13 Linux glibc 2.28+ x86-64 abi3
SHA-256 checksum
How to use checksums
0fd09009c491934c34675c1ebc93a08ab70978fa0b45b911a3f6772ce9f31dbb
BLAKE2b-256 checksum
How to use checksums
06fd5bd36cf4d4efa142131624e1e620c5fa8ec520c3c24063c853ba47f8144d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 3, 2026.

Transparency log

Release files / cc_transcript-14.46.7-cp313-abi3-manylinux_2_28_aarch64.whl

Download URL cc_transcript-14.46.7-cp313-abi3-manylinux_2_28_aarch64.whl
Size 23.9 MB
Tags CPython 3.13 Linux glibc 2.28+ ARM64 abi3
SHA-256 checksum
How to use checksums
b02c2a60e3a88892722411d730927ad6c776d13fb5ca6928aa761c8d1fcfd0e2
BLAKE2b-256 checksum
How to use checksums
f3ca2a06d4b57ea94b056f3c32eec4e68c7054b39adb1b1051f9f113084ccb1b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 3, 2026.

Transparency log

Release files / cc_transcript-14.46.7-cp313-abi3-macosx_11_0_x86_64.whl

Download URL cc_transcript-14.46.7-cp313-abi3-macosx_11_0_x86_64.whl
Size 24.7 MB
Tags CPython 3.13 abi3 macOS 11.0+ x86-64
SHA-256 checksum
How to use checksums
66bf9d90a290bba0646e8574b5d5451d21dd59a6d567b1d0284bf1f59828eace
BLAKE2b-256 checksum
How to use checksums
6b38b2629c870e1196913bc0480c76a5266ea0ac613a0d723ced3a11ad1df6c7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 3, 2026.

Transparency log

Release files / cc_transcript-14.46.7-cp313-abi3-macosx_11_0_arm64.whl

Download URL cc_transcript-14.46.7-cp313-abi3-macosx_11_0_arm64.whl
Size 23.6 MB
Tags CPython 3.13 abi3 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
4a9971e41f4ff05a77c65ae2b4fbf6896ec6297b75469ad922f0ad1e24597d3d
BLAKE2b-256 checksum
How to use checksums
51a7437d81ebdef34da363aa47e6dd1136abd8262c9bb2affc1d9b490a665aa7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 3, 2026.

Transparency log

Security for cc-transcript 14.46.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Full provenance

All 5 files in this release have been uploaded with provenance metadata.

Select from 5 files

Attestation for cc_transcript-14.46.7.tar.gz

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 3, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

14.46.7 This release

5 release files Full provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page