Claude Code starts every session cold. Recall keeps a local log of your sessions and condenses it into a resume-ready summary —
entirely on your machine. No API key, no external model, nothing sent anywhere. It's built for people running Claude Code locally on a subscription: the only AI in the loop is Claude Code itself; the summarization is done by a classical Python summarizer.
Free on your subscription. It solves the cold-start problem — no more re-explaining the project each session — without a metered summarizer running up a bill. The summary is a local algorithm, not an LLM call, so persistent memory costs you nothing beyond the subscription you already pay for.Saves your usage credits. Two ways: (1) the summary is built locally, so capturing and updating your memory spendszero model tokens; and (2) resuming from a compactcontext.md
(~1–2K tokens) instead of re-explaining the project from scratch each session means far fewer tokens spent per session — stretching your subscription's usage limits (or, on the API, lowering billed credits).Nothing leaves your machine. Your transcripts (code, paths, sometimes secrets) are never sent to any API. Most "memory" tools pipe your context to a model endpoint; Recall makes a privacy guarantee they can't.Zero-friction. Nopip install
, no local model to run, no key to configure, works offline. It starts working the moment the plugin loads.
Two files, written into your project under .recall/
:
—history.md
*the log.*Append-only. Every session is captured here as it happens (your prompts, Claude's replies, the files touched and commands run).—context.md
*the summary.*Overwritten by the local summarizer — the condensed "where are we right now" you load into the next session: goal, summary,next steps / open threads, files touched, and where you left off.
| Moment | What happens |
|---|---|
| During the session | |
The Stop / SessionEnd hooks append new activity to .recall/history.md . Capture is incremental (only new turns) and fully local. |
|
| At session start | |
The SessionStart hook surfaces context.md and has Claude ask you two things: resume from the saved context? and keep logging this session? |
|
| Before you wrap up | |
You run /recall:save . The local summarizer reads history.md and (over)writes context.md . |
|
| …or automatically | |
Set auto_save_context: "on_end" and context.md regenerates every time a session ends — no /recall:save needed. |
There is no LLM call anywhere — the summary is produced by TF-IDF + TextRank (extractive summarization) running locally.
scripts/summarizer.py
ranks the most central sentences of your session:
- TF-IDF sentence vectors
- a cosine-similarity graph between sentences TextRank— PageRank power iteration over that graph — to score sentences- the top Nare kept in original order
context.md
wraps that summary with deterministic facts pulled straight from the
transcript and git: the goal (your first ask), files touched, commands run, where
you left off, and git diff --stat
.
No installs required. The whole TF-IDF + TextRank implementation is vendored
in summarizer.py
. If numpy
happens to be importable it's used to vectorize the math (faster on big sessions); if not, an identical pure-Python TextRank runs instead. Same algorithm, same result — numpy is an optional accelerator, never a requirement. The save output tells you which path ran.
/recall:save
— run the local summarizer → (over)writecontext.md
./recall:show
— printcontext.md
./recall:log
— tailhistory.md
.
Drop this in your project root to override defaults:
| Key | Default | Purpose |
|---|---|---|
output_dir |
||
".recall" |
||
Where history.md / context.md live. |
||
capture_history |
||
true |
||
Append session activity to history.md . |
||
auto_save_context |
||
"off" |
||
Regenerate context.md when a session ends: "off" or "on_end" . |
||
summary_sentences |
||
8 |
||
| How many sentences the summary keeps. | ||
redact |
||
true |
||
| Strip obvious secrets before writing the md files. | ||
include_git |
||
true |
||
Add git diff --stat + recent commits to context.md . |
||
max_input_chars |
||
200000 |
||
| Cap on text fed to the summarizer (oldest dropped). |
** logging** for a project without editing config: create
.recall/.capture-d
. Delete it to resume.
Recall makes no network calls, uses no API key, and loads no third-party
model. The summarizer is local Python; the hooks are stdlib-only (numpy is an
optional accelerator). It reads your session transcript and writes only under
output_dir
. Concretely:
No credentials, ever. The plugin has zero references to API keys, auth,ANTHROPIC_*
, or HTTP. Ifclaude
itself shows*"Invalid API key"*, that's the CLI's own auth — usually a staleANTHROPIC_API_KEY
env var shadowing your subscription login.unset ANTHROPIC_API_KEY
(or runenv -u ANTHROPIC_API_KEY claude …
). It has nothing to do with Recall.Redaction. A best-effort pass strips common secret shapes (API keys, tokens,.env
assignments, PEM keys) before writing, sincecontext.md
/history.md
may be committed. Best-effort, not a guarantee — review before committing.Hardened git.git diff
/log
are run withcore.fsmonitor
,diff.external
, hooks, and the pager disabled, so an untrusted cloned repo can't use its own git config to execute code when Recall reads ground-truth. Setinclude_git: false
to skip git entirely.Confined writes.output_dir
is forced to stay inside the project; a project-shipped config can't redirect writes to an absolute path or../..
.Scoped transcript. Recall only reads the transcript for the current project (matched by cwd); it never falls back to another project's sessions.Trust boundary for shared memory.context.md
is injected into the model at session start. If youcommit, treat it like any other shared input: a teammate (or a bad actor with repo write access) could craft a.recall/
as shared team memorycontext.md
to attempt prompt-injection. SessionStart fences the content and labels it untrusted data, and Claude asks before relying on it — but if you don't fully trust who can write the repo, keep.recall/
git-ignored (the default).
Both are fine. Commit it for shared team memory, or git-ignore it for personal
memory (.gitignore
ships ignoring it by default — flip the comment to commit).
From the marketplace (this repo is its own marketplace):
/plugin marketplace add raiyanyahya/recall
/plugin install recall@recall
Local dev (no install step):
claude --plugin-dir /path/to/recall
No pip install
— the summarizer is vendored and stdlib-only (numpy used as an
optional accelerator if present). Work a session, run /recall:save
, and open a fresh session — Recall greets you with where you left off.
python -m venv .venv && . .venv/bin/activate
pip install pytest ruff bandit numpy # numpy optional
ruff check scripts tests # lint
bandit -c pyproject.toml -r scripts # security static analysis
pytest # run the suite (also test without numpy)
claude plugin validate . # official manifest validation
CI (.github/workflows/
) runs lint + Bandit, the test suite across Python 3.9–3.13 with and without numpy (both summarizer paths), CodeQL, secret scanning, and manifest JSON validation on every push and PR. See CONTRIBUTING.md and SECURITY.md.
recall/
├── .claude-plugin/plugin.json # manifest
├── hooks/hooks.json # SessionStart (ask/resume) · Stop+SessionEnd (capture)
├── commands/ # /recall:save · show · log
├── scripts/
│ ├── summarizer.py # vendored TF-IDF + TextRank (numpy optional)
│ ├── make_context.py # build/overwrite context.md
│ ├── capture.py # append session activity to history.md
│ ├── session_start.py # surface context + ask the start questions
│ ├── parse_transcript.py # transcript → events + renderers
│ └── config.py · common.py · redact.py
├── tests/ # pytest suite (summarizer, capture, security, …)
├── .github/ # CI, CodeQL, secret scan, dependabot
├── recall.config.json # config template / defaults
├── pyproject.toml # ruff / pytest / bandit config (no runtime deps)
├── LICENSE · SECURITY.md · CONTRIBUTING.md
└── .gitignore
Bugs and ideas are welcome — open an issue (bug-report and feature templates provided) or a pull request. See CONTRIBUTING.md before submitting, and report security vulnerabilities privately per SECURITY.md rather than in a public issue.