Agent Collab Skills

Agent Collab Skills

繁體中文 · Public harness contract · Native lanes · 0.6 migration · 0.5 goal-slice migration · 0.4 migration

Provider-neutral collaboration skills plus an optional, standard-library-first
Python harness for bounded, resumable, human-authorized agent work.

This project is a governance layer, not a general agent runtime. A host supplies
models, tools, sessions, sandboxes, and tracing. Agent Collab supplies portable
roles, policy evaluation, checkpoints, proposal-only memory, reconciliation,
and acceptance evidence.

Architecture

The deterministic layer controls state and limits. Agents produce prose,
implementation, review, and synthesis. A human remains responsible for
breaking contracts, memory promotion, semantic acceptance, and shipping.

Skills

Each skill fires on a situation, not only on a request:

Redirect stubs, removed in 0.7.0 (migration 0.6):
agent-output-reconciler → agent-acceptance-gate;
agent-shared-memory → agent-context-budget;
agent-plan-act-reflect → deprecated, its harness loop now lives in
agent-context-budget.

Native mode and harness mode

Native mode is the default. When every lane runs inside one host session with
the user present, the lane table and briefs live in the conversation, the
host's own limits and permissions apply, and no plan, packet, or checkpoint is
written to .coord/ (only a memory proposal may be).
Native lanes maps the roles to Claude Code's Agent,
SendMessage, Workflow, and worktree mechanisms.

Harness mode adds the policy and checkpoint contract below when a round spans
sessions or tools, runs unattended, must resume after an interruption, needs a
signed human gate, or AGENT_COLLAB_POLICY is configured. A configured policy
always applies and fails closed when unreadable.

Public harness…