Skill Orchestrator

Skill Orchestrator

Single entry point for multi-skill workflows. You plan the sequence, choose an execution mode, run each specialist skill, and hand off via CW-AIP — without collapsing research into decisions or skipping skill boundaries.

Execution mode

skill-orchestrator-multiagent is a thin alias for execution_mode=isolated_subagents. Do not maintain a divergent planning model there.

Optional context preflight: when the goal depends on current multi-source CometWeb state, run cometweb-context first and pass the ContextEnvelope as a dependency.

Boundaries

Owns:

• workflow archetype selection,
• execution_mode selection,
• ordered execution plan with envelope types,
• loading each step's SKILL.md (or launching a subagent that does),
• handoff summaries between steps,
• final workflow result (artifacts produced, gaps, what remains).

Does not own:

• Evidence Pack construction (Evidence Researcher),
• GO/NO-GO / Council deliberation (AI Council),
• release gate verdicts (Release Readiness),
• weekly priority reconciliation (Product Operator),
• domain findings (auditors, CI, SEO, etc.),
• ContextEnvelope construction (cometweb-context).

Read references/workflow-archetypes.md and references/sequencing-rules.md. For isolated mode also read references/multiagent-execution.md (shared with the alias).

Workflow

1. Plan

Run the kernel when the host allows:

python3 scripts/orchestrate_kernel.py "<user goal>" --json

If scripts are unavailable, infer the same archetype from the goal using references/workflow-archetypes.md.

Present the plan before step 1 unless the user asked to run immediately:

Workflow plan (research_then_council) · execution_mode=auto→isolated_subagents
  1. evidence-researcher — Evidence Pack
  2. ai-council — DecisionHandoff

2. Confirm scope (lightweight)

If the plan includes ai-council and the user did not mention a decision, ask once: material decision in scope, or evidence-only?

If release-readiness is included without a pinned RC/build + environment, stop and request the pin before gating.

3. Execute steps

single_thread — for each step (see references/sequencing-rules.md):

1. Read that skill's SKILL.md.
2. Execute its full workflow (scripts, validators, output contract).
3. Emit the CW-AIP envelope for the step.
4. Handoff summary before the next step.

isolated_subagents — for each step:

1. Build subagent payload (scripts/orchestrate_multiagent_kernel.py when available).
2. Launch host Task/subagent; do not run domain work in the parent.
3. Validate returned envelope type; append to prior_envelopes.

Protocol: protocol/cw-interchange-v1.md (prefer CW-AIP v2 wrappers when producers emit them).

4. Close

Emit Workflow result:

• archetype used,
• execution_mode resolved,
• envelope IDs / hashes per step,
• accepted vs gap claims (if research ran),
• Council verdict if Council ran (otherwise explicitly not run),
• recommended next single skill if work continues.

Archetype quick reference

Output contract

1. Workflow plan — archetype + ordered steps + execution_mode
2. Step outputs — one subsection per step with envelope type and pointer
3. Workflow result — synthesis without overstepping skill boundaries
4. CW-AIP handoff block — JSON or structured list of envelope metadata when useful

Never fold Evidence Researcher synthesis into a Council GO/NO-GO in the same step.