agent-team v0.6.1

Added

• The product vision: VISION.md tells the team what the product should be. Every workflow
  receives it with the README, and discuss gives it its own section, so the roadmap is planned
  towards it. init asks for it first (or --vision TEXT|FILE); discuss --vision FILE plans from
  a file anywhere and saves it as VISION.md when there's none. /team-init and /team-plan ask
  for it when it's missing.

Changed

• discuss no longer needs a topic: the default is "next milestones".

agent-team v0.6.0

Added

• agent-team init asks, in a terminal, where the models run (Claude with Ollama builders, only
  Ollama, or only Claude), which optional members to add, how many builders and any spend limits,
  then shows the team and asks before writing. Flags answer the same questions for scripts:
  --models, --members, --builders, --per-run, --per-day; --yes takes the defaults.
  /team-init passes the answers it collects as these flags.
• init finds Ollama by itself: on this machine, at OLLAMA_HOST, on the machine a VM or
  container runs on (Parallels, VirtualBox, UTM, Docker, Lima) or at the gateway.
  agent-team discover --ollama lists what it finds.
• The dashboard's Settings has a Team composition card with the same choices for an existing
  team, including Find Ollama and a model list from the chosen server, shown as a diff first.
• Tab completion for bash and zsh: commands, options, choices and the team's member names.
  The installer sets it up for bash; agent-team completion install does it for zsh.
• install.sh --uninstall --purge also deletes the saved keys and project list (asking first).

Changed

• install.sh --uninstall says where your saved keys are kept, and warns when another copy (such
  as a pipx install) is still on the PATH. Its list of slash commands is complete.

• agent-team carries the Lakeba brand, as an open-source project Lakeba shares with its partners,
  clients and the developer community: the website, the dashboard and the README use the Lakeba
  mark and colours, with a "Conceive. Create. Commercialise." section, a "Shared by Lakeba"
  section, a favicon and a social preview image.

Fixed

• agent-team init --ollama-url URL in a project that already has a team file now points that
  team's Ollama connection at URL (keeping the rest of the file) instead of refusing and leaving
  ready checking localhost.
• init picks pytest for a Python project only when the project uses it; otherwise it runs
  unittest discovery in the tests folder. It writes python3, since many Linux machines have no
  python.
• The website's "Get started" cards no longer overflow the page width on narrower screens.

agent-team v0.5.1

Changed

• The Anthropic key is optional: the readiness checklist shows it as optional (○) until members
  use Claude, and only counts connections a member actually uses. The installer, README and
  /team-init no longer present it as a required step.

Added

• agent-team init --no-claude puts every member on Ollama (this machine or another one), with
  no Claude connection and no key; the dashboard's Settings has a matching "Local only" template.

agent-team v0.5.0

The first release. agent-team is a configurable team of AI agents that plans, builds, reviews,
fixes, merges, releases and markets a software project through GitHub, with members on any
model and any machine. It grew out of the scripts that built todo-py v1.0.0 and v1.0.1.

The team

• Teams are described in .team.toml: any number of members and roles, files owned per member,
  per-member skills (Markdown files or Claude Code skill folders), and team memory: reviewers'
  LESSON: lines are kept and shown to every member in later work.
• Members can be on Claude (anthropic), Ollama (local or another machine), any OpenAI-compatible
  server, or another machine running agent-team serve (token-protected; nodes can be found on the
  local network with agent-team discover). Every kind can call tools, so any member can run the
  devops shift.
• Roles the workflows use: lead, builder, devops, marketing, fact-check, and optional QA (writes
  tests first), security (reviews every approved build) and docs (updates the docs).

Workflows

• discuss (a roadmap the members agree, reading the devops feedback digest), build (the lead
  plans, builders implement with search/replace edits, tests run, the lead reviews with tools to
  read files and run tests; --parallel splits a plan across builders), ship (one devops shift:
  triage, sign-offs, reviews, fixes, merges, releases), fix (apply a review to an open PR),
  setup, market and autopilot (work through a milestone a PR at a time).
• GitHub issues labelled team:build are the team's to-do list (agent-team issues sync creates
  them from the roadmap); autopilot builds them and its PRs close them.
• Scheduled shifts (agent-team schedule --every 6h, launchd or cron, never two at once) and
  background runs (agent-team jobs, the dashboard, the Claude panel).

Guardrails

• Merges need green CI, the lead's approval and every owner's sign-off on the exact head commit;
  paths in require_approval also need the owners' approval of that commit
  (agent-team approve <PR>); release = "ask" makes releases proposals the owners approve.
• Re-reviews block only on points still open or problems the new commit introduces.
• Every push is checked for secrets first; text from outside the team reaches the models marked
  as untrusted; members can post as their own GitHub accounts (github_token_env) so their
  reviews are real GitHub reviews.
• [sandbox] mode = "container" runs the code the team writes in a throwaway container with no
  network and none of your keys.
• Guardrail scenario tests run whole shifts against a stand-in GitHub.

Cost and models

• Every model call is recorded with its tokens and an estimated cost; spend limits per run, per
  day and per milestone stop a run before the next call; agent-team estimate predicts a run's
  cost from past runs; agent-team scoreboard shows approval rates, rounds and cost per member.
• Routing: a member hands its work to a stronger one after rejected rounds (escalate_to), and
  routine checks can use a cheaper model ([routing].light_model).
• Focused context for big projects: a ranked shortlist of relevant files and a map of the rest.
• agent-team eval runs fixed scenarios with your real models in a throwaway project.

Dashboard and Claude Code

• agent-team ui: Overview, Team (edit everything, add a machine, review the diff before saving),
  Runs (start and follow runs), Costs (with the scoreboard), Activity (live charts), Settings (easy
  switches and team templates) and Projects (every project on this Mac).
• A Claude Code plugin: /team-init, /team-doctor, /team-plan, /team-build, /team-fix,
  /team-ship, /team-autopilot, /team-issues, /team-schedule, /team-market, /team-ui,
  /team-run, and a side panel (/team-panel) with the team, health, runs, spend and approvals.
• [notify] posts to Slack or any webhook when PRs open or merge, approvals or releases wait,
  autopilot stops, a spend limit is hit or a run fails.

Setup

• agent-team ready lists what a machine and project still need, each with its fix; init detects
  Python, Node (Jest, Vitest, Mocha, node --test), Go, Rust and .NET projects, and Ollama on
  another machine; agent-team keys set keeps API keys where every command finds them.
• One-command installer for macOS and Linux (scripts/install.sh), and this release on PyPI
  (pipx install agent-team).