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 14.46.5

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 14.46.5
File Size Uploaded Provenance Actions
cc_transcript-14.46.5.tar.gz 12.9 MB With provenance Details for cc_transcript-14.46.5.tar.gz

Built distributions (wheels)

Table of built distributions (wheels) for cc-transcript 14.46.5
File Actions
cc_transcript-14.46.5-cp313-abi3-manylinux_2_28_x86_64.whl CPython 3.13 abi3 Linux glibc 2.28+ x86-64 Details for cc_transcript-14.46.5-cp313-abi3-manylinux_2_28_x86_64.whl
cc_transcript-14.46.5-cp313-abi3-manylinux_2_28_aarch64.whl CPython 3.13 abi3 Linux glibc 2.28+ ARM64 Details for cc_transcript-14.46.5-cp313-abi3-manylinux_2_28_aarch64.whl
cc_transcript-14.46.5-cp313-abi3-macosx_11_0_x86_64.whl CPython 3.13 abi3 macOS 11.0+ x86-64 Details for cc_transcript-14.46.5-cp313-abi3-macosx_11_0_x86_64.whl
cc_transcript-14.46.5-cp313-abi3-macosx_11_0_arm64.whl CPython 3.13 abi3 macOS 11.0+ ARM64 Details for cc_transcript-14.46.5-cp313-abi3-macosx_11_0_arm64.whl

Total release size: 110.1 MB

Release files / cc_transcript-14.46.5.tar.gz

Download URL cc_transcript-14.46.5.tar.gz
Size 12.9 MB
Tags Source
SHA-256 checksum
How to use checksums
1604341000ff33dad0846bacb3f598dbe553aa500cdd3109645317990459c497
BLAKE2b-256 checksum
How to use checksums
3f3459c46de8abd5b232d0e97d22c145a6093402e15f139f05a0d2c813a7f9f9
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 2, 2026.

Transparency log

Release files / cc_transcript-14.46.5-cp313-abi3-manylinux_2_28_x86_64.whl

Download URL cc_transcript-14.46.5-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
8cc7eabee899bd62b5ca67bf23a6e6e9d26e5f99e08678d2ee9bc8aa0a7ed114
BLAKE2b-256 checksum
How to use checksums
ab2d6a083dc9c7f0116d906adeda577ae861d7beb2bbe4907373a5a649a1acbb
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 2, 2026.

Transparency log

Release files / cc_transcript-14.46.5-cp313-abi3-manylinux_2_28_aarch64.whl

Download URL cc_transcript-14.46.5-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
c528c900fa2bdde688878ec96d1d1e9a91d4edb0aee2703316a5a02cc4be5eb0
BLAKE2b-256 checksum
How to use checksums
d591b2b7027f25fc48bff451f7da396b1c0c4538015a15541fabe51b97bbb3ec
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 2, 2026.

Transparency log

Release files / cc_transcript-14.46.5-cp313-abi3-macosx_11_0_x86_64.whl

Download URL cc_transcript-14.46.5-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
304c82439b6b09fdbc63696f6c24ae0bb0897d3ef32a4b767d0b3de08ac85ac4
BLAKE2b-256 checksum
How to use checksums
4b77d18fba06ab4cf905e31aa1b4dce64f17bddb70d7de483ca8f63f0e199dd4
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 2, 2026.

Transparency log

Release files / cc_transcript-14.46.5-cp313-abi3-macosx_11_0_arm64.whl

Download URL cc_transcript-14.46.5-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
629b86170e1e42af0ae8e2b8c7308c2ada506b3a4709cdcd055219c8d909c581
BLAKE2b-256 checksum
How to use checksums
adc9e63f5e6afcbb87f6b54331e463f218a5e5cdc7afd37ad28a3352e0bd155c
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 2, 2026.

Transparency log

Security for cc-transcript 14.46.5

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-14.46.5.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 2, 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

14.46.5 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