league-of-agents 0.9.2

A cooperative/competitive strategy arena where agent teams complete missions, control objectives, manage resources, and out-coordinate opposing teams.

league-of-agents

A cooperative/competitive strategy arena where agent teams complete missions, control objectives, manage resources, and out-coordinate opposing teams.

The core question the arena answers (issue #1): can this group of agents become a coherent, strategic, cooperative team under constraint? Matches are deterministic and replayable, scored on both mission outcome and cooperation quality, beautiful for humans and --json-practical for agents.

What you get

• A deterministic arena engine (league/engine/) — immutable match state, an append-only event log as the single source of truth, and a pure seedable tick: same declared actions + same seed → same outcome, enforced by a CI determinism gate.
• Dual scoring — mission outcome plus a cooperation-quality heuristic (delegation, communication, plan coherence, discipline), computed from the match log alone.
• A published tempo axis — per-team speed, converted against a per-substrate calibration baseline with raw latency always shown beside it; see docs/tempo-methodology.md for the calibration, the conversion, and its limits.
• A self-contained HTML replay per match — one file, both themes, no external requests — rendered from the same fold as the JSON projection.
• An agent-first CLI cited from teken: every write verb is dry-run by default (--apply commits), every read verb takes --json, no third-party runtime dependencies.
• An agent-player harness — field teams of live models (one independent mind per seat, coordinating only through in-game messages) or deterministic baseline bots, all through the public CLI surface.
• A mesh identity + the guildmaster skill kit — culture.yaml, AGENTS.colleague.md, and 11 vendored skills under .claude/skills/ (see docs/skill-sources.md).

Quickstart

uv sync
uv run pytest -n auto                 # run the test suite
uv run league whoami                  # identity from culture.yaml
uv run league learn                   # self-teaching prompt (add --json)
uv run teken cli doctor . --strict    # the agent-first rubric gate CI runs

Play a full bot-vs-bot match end to end:

uv run league team register blue --agent b1:bot:greedy:scout \
    --agent b2:bot:greedy:harvester --agent b3:bot:greedy:defender --apply
uv run league team register red --agent r1:bot:greedy:scout \
    --agent r2:bot:greedy:harvester --agent r3:bot:greedy:defender --apply
uv run league match new --scenario skirmish-1 --team blue --team red \
    --seed 7 --id my-first-match --apply
uv run league match act my-first-match --team blue \
    --action b1:move:2,1 --plan "scout east" --apply
uv run league match act my-first-match --team red \
    --action r1:move:9,8 --apply        # last team in -> the turn resolves
uv run league match show my-first-match --json
uv run league match replay my-first-match > match.html   # open in a browser
uv run league match score my-first-match

Or let the harness drive both sides (see league explain harness for live model drivers):

uv run league harness run --config docs/playtests/season-0/opener.config.json --apply

Or skip the hand-authored setup entirely: league play bundles every documented mode as a preset (league play list), so each one launches with a single command (league play show <preset> prints the resolved config first if you want to check before applying):

uv run league play start solo-vs-bot --apply          # one agent, handicapped, vs the house bot
uv run league play start team-vs-bot --apply          # one mind per seat (stateless) vs the house bot
uv run league play start team-vs-team --apply         # bot-file vs bot-file, fully offline
uv run league play start orchestrator-vs-bot --apply  # a master mind + per-seat ground agents vs the house bot
uv run league play start resident-vs-bot --apply      # one long-lived session per seat vs the house bot

CLI

Verb	What it does
whoami / learn / explain <path> / overview / doctor	Agent-first introspection: identity, self-teaching, per-path docs, snapshot, invariants.
arena list|show	The scenario catalog (read-only).
team register|list|show	Rosters: agent seats as id:model:role triples.
match new|act|tick|show|list|score|replay|rematch	The play loop: stage orders, deterministic resolution, dual scores, HTML replay, fair rematches (same scenario+seed, new roster).
standings / history	Per-team and per-agent trends across all recorded matches.
harness run	Play a configured match with live drivers end to end.
play list|show|start	One-command launch of a bundled preset mode (solo/team/orchestrator/resident vs. the house bot).

Every read verb supports --json; write verbs (team register, match new/act/tick/rematch, harness run, play start) are dry-run by default — --apply commits. Results go to stdout, errors/diagnostics to stderr (never mixed). Exit codes: 0 success, 1 user error, 2 environment error, 3+ reserved.

How the game grows

Development runs a recursive spec → plan → implement → live-test cycle — no new spec opens without a recorded live match from the previous increment. See docs/process/cycle.md; season-0 artifacts live in docs/specs/, docs/plans/, and docs/playtests/.

License

Apache 2.0 — see LICENSE.