Terminal client for the Briar agent-orchestration API.
Project description
briar
Turn the live state of your tools into agent-ready context — then let autonomous agents act on it. All on your machine.
briar is a local-first Python CLI that mines what's actually happening across your stack — GitHub, Bitbucket, AWS/GCP/Azure, Jira, Linear, Fireflies — into a knowledge store, keeps it fresh on a schedule, and runs LLM agents that fix PRs and ship tickets against it.
No SaaS, no remote workspace, no data leaving your laptop. Your credentials, your machine, your APIs — briar just shells out to them directly and writes the results to local markdown or Postgres.
pip install briar-cli
briar version
Why briar
- 🔒 Local-first. Everything runs on your machine against your own API tokens. Nothing is uploaded to a service.
- 🔌 One CLI, every system. GitHub · Bitbucket · AWS · GCP · Azure · Jira · Linear · Fireflies — behind a single, consistent interface.
- 🧠 Context, not dashboards. Extraction produces clean markdown knowledge an LLM (or a human) can actually read — PR archaeology, codebase conventions, infra inventory, reviewer profiles, meeting digests.
- ⏰ Cron, replaced. An in-process scheduler keeps per-company knowledge fresh with one long-running command.
- 🤖 Agents that do the work. Point an agent at a PR to address review comments, or at a ticket to implement it end-to-end — branch, code, open a draft PR.
- 🗺️ Plans from your board. Turn a Jira/GitHub Projects board into an ordered, LLM-synthesised implementation plan and run it card by card.
Quickstart
pip install briar-cli
# 1. Authenticate the providers you'll use (tokens land in ~/.config/briar/secrets.env)
briar auth login github-pat --company acme
briar auth login jira-token --company acme
export ANTHROPIC_API_KEY=sk-ant-... # LLM key comes from the environment
# 2. Mine a repo's PR history into a knowledge blob
briar extract --company acme \
--include pr-archaeology \
--pr-repo acme-co/acme-app --pr-max 50
# 3. Read it back
briar context get knowledge:acme
Telemetry:
briarships with opt-out error/usage analytics (Sentry). No prompts, file contents, ticket keys, repo names, paths, or secret values ever leave the machine. Turn it off any time withbriar telemetry off,BRIAR_TELEMETRY=off, orDO_NOT_TRACK=1.
What you can do
briar extract — mine live state into knowledge
# PRs + AWS infra in one shot, filtered to your team
briar extract --company acme \
--include pr-archaeology --include aws-infra \
--pr-repo acme-co/acme-app \
--pr-authors-allow alice --pr-authors-allow bob \
--aws-extract-region us-east-1 \
--aws-extract-service ecs --aws-extract-service rds
# Last 14 days of Fireflies meeting summaries for an attendee list
FIREFLIES_ACME_API_KEY=ff_xxx briar extract --company acme \
--include meeting-digest --meeting-since-days 14 \
--meeting-attendee-allow alice@acme.com
briar runbook serve — scheduled extraction, in-process
Describe every company + task in one YAML and let briar run the schedule forever — no cron, no external job runner.
briar runbook serve runbooks/
briar agent — autonomous LLM flows
# prfix: read a PR's open review comments, push fixes, reply inline
briar agent prfix \
--company acme --owner acme-co --repo acme-app \
--pr 42 --branch fix-typo \
--runbook runbooks/acme.yaml
# implement: take a ticket end-to-end — clone, branch, code, open a draft PR
briar agent implement \
--company acme --owner acme-co --repo acme-app \
--ticket-project ACME --ticket-key ACME-42 --tracker jira \
--runbook runbooks/acme.yaml
# Preview the exact prompt + tools without spending a token
briar agent prfix --company acme --owner acme-co --repo acme-app \
--pr 42 --branch fix-typo --dry-run
briar plan — LLM-driven implementation plans from a board
# Build an ordered plan from a GitHub Projects board, with company knowledge spliced in
briar plan build https://github.com/orgs/acme/projects/1 \
--name acme-q3 --company acme --llm anthropic --with-knowledge
# Run the loop: the selector picks the next card, the engineer agent ships it,
# the knowledge store learns what changed — card by card.
briar plan run acme-q3 \
--company acme --owner acme-co --repo acme-app \
--tracker github-issues --llm anthropic
# Smoke one card with --dry-run before letting the loop go wide
briar plan run acme-q3 --limit 1 --dry-run --llm anthropic \
--company acme --owner acme-co --repo acme-app
briar scaffold — JSON config bundles for downstream tools
briar scaffold implementation \
--prefix acme-impl --source github \
--owner acme --repo widgets
Plus briar context (local knowledge blobs), briar dashboard (read-only HTML status page), briar secrets doctor (credential coverage), and briar journal (decision-journal inspection).
Repeatable flags — fan out across repos, projects, services
Most list-style flags accept multiple occurrences: repeat the flag, once
per value (there's no comma form — --pr-repo a,b is one repo named
a,b). Mix them to cover a whole fleet in a single command.
# Mine several repos, keep the team's PRs, drop the bots, across two boards.
# --pr-max applies per repo; author allow/block compose as allow ∩ ¬block.
briar extract --company acme \
--include pr-archaeology --include active-tickets \
--tracker jira \
--pr-repo acme-co/web --pr-repo acme-co/api --pr-repo acme-co/mobile \
--pr-max 75 \
--pr-authors-block "dependabot[bot]" --pr-authors-block "renovate[bot]" \
--ticket-project ACME --ticket-project PLAT
# Scaffold a triage flow from two sources, filtered by author + assignee.
# Each tracker source carries its own repeatable *-authors/assignees-*.
briar scaffold implementation --prefix acme-triage \
--source github --source jira \
--owner acme-co --repo acme-app --github-secret-id <uuid> \
--github-authors-block "dependabot[bot]" \
--github-assignees-allow alice --github-assignees-allow bob \
--jira-project ACME --jira-project PLAT --jira-secret-id <uuid> \
--auth-mode pat
The same lists map onto runbook YAML as arrays — e.g. pr_repo: [acme-co/web, acme-co/api] is two --pr-repo flags.
Handy patterns
# Script briar: --format json pipes straight into jq (works on every command).
briar plan status acme-q3 --format json | jq -r '.blocked[].key'
# Gate CI on credential coverage — exits non-zero if any runbook is missing creds.
briar secrets doctor --examples runbooks/
# Cost-safe agent rollout: preview for free, then one paid card, then go wide.
briar agent implement --company acme --owner acme-co --repo acme-app \
--ticket-project ACME --ticket-key ACME-42 --dry-run
briar plan run acme-q3 --company acme --owner acme-co --repo acme-app \
--tracker jira --llm anthropic --limit 1 --max-iter 20
Install options
pip install briar-cli # base: GitHub/Bitbucket/AWS, Jira/Linear, Anthropic + Bedrock, file + Postgres stores
pip install 'briar-cli[openai]' # OpenAI LLM
pip install 'briar-cli[gemini]' # Google Gemini LLM
pip install 'briar-cli[gcp]' # GCP cloud provider
pip install 'briar-cli[azure]' # Azure cloud provider
pip install 'briar-cli[vault]' # HashiCorp Vault credential store
pip install 'briar-cli[infisical]' # Infisical credential bootstrap
pip install 'briar-cli[all]' # everything
Each adapter fails loudly with the right install command if its SDK is missing. Python 3.10+ (tested through 3.12).
Documentation
Full command reference, every flag, runbook-YAML schema, configuration, and recipes:
A comprehensive multi-company runbook lives in examples/all_features.yaml.
License
See LICENSE.
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