orchestrating-work

name	orchestrating-work
description	Principles for multi-agent workflow execution. Use when coordinating agents, accepting or rejecting agent work, executing producer-critic cycles, or running any multi-phase orchestrated task.

Orchestrating Work

Execution principles for multi-agent workflows: input validation, work acceptance, file organisation, and phase transitions. Workflow structure (which phases to run) lives in designing-workflow.

1. Validate Inputs Before Invocation

Agents need complete context to work independently — every missing input costs a clarification round-trip.

Universal requirements for ALL agents (read agents/<agent-name>.md for agent-specific ones):

• Absolute path to work/<task-id>/ directory
• Absolute output path for the deliverable
• All dynamic skills provided as file paths or inline content, never just names. Preloaded skills (listed in the agent's skills frontmatter) are injected automatically.
• All agent-specific required inputs present
• All paths absolute (no ./ or ../)

Before invoking: check universal requirements, read the agent's file for specific ones, then wait for the agent to echo its inputs.

If validation fails: STOP, identify and provide the missing inputs, re-validate before re-invoking. If the agent does not echo inputs: STOP — silence indicates malformed or truncated instructions; verify and re-invoke.

2. Accept or Reject Work Deliberately

Rejecting work during review costs one iteration cycle; accepting substandard work costs post-deployment rollback and rework.

Universal criteria for all artefacts:

• Output file exists at declared path; not empty or truncated
• Basic structure present; assigned task addressed completely, not partially or tangentially
• No TODO markers or placeholders (unless explicitly planned for next iteration)
• Brief requirements addressed (cross-reference the brief checklist if one exists)

Then apply artefact-type standards from the governing skill:

Artefact type	Reference skill
Skills (SKILL.md)	writing-skills
Research outputs	conducting-research
Reviews (critic outputs)	assessing-quality
Briefs	creating-briefs

Base the decision on the checklists, not impressions. On rejection: give the agent clear, actionable guidance on the specific issues plus the path to the previous version, re-invoke, and do NOT advance to the next phase until work is accepted.

3. Organise Files Systematically

Consistent naming lets a workflow be reconstructed from its artefacts alone: artefact_v1 → review_v1 → artefact_v2 → review_v2 is the iteration history.

Task ID: {type}-{subject} (e.g. skill-api-documentation, report-q4-summary) — lowercase letters, numbers, hyphens; under 64 characters; specific enough to distinguish from similar tasks.

Work directory:

work/<task-id>/
├── brief.md
├── research_brief.md (optional)
├── source_index.md (optional)
├── sources/ (optional)
├── research_v1.md (optional)
├── artefact_v1.md
├── artefact_v2.md
├── review_v1.md
├── review_v2.md
└── learning_proposals.md

File naming:

File type	Format
Artefacts	artefact_v{N}.{ext}
Artefact reviews	review_v{N}.md (version matches artefact)
Research	research_v{N}.md
Research reviews	review_research_v{N}.md
Briefs	brief.md / research_brief.md
Source index	source_index.md
Learning proposals	learning_proposals.md

Versioning: start at v1; sequential integers, no gaps, no decimals; never overwrite — create a new version instead. Each artefact version gets a matching review version. New version = new review cycle (after critic feedback or a significant requirement change) — not for typo fixes or internal refinement before first review.

4. Verify Phase Prerequisites Before Transitions

Advancing without completing prerequisites bakes wrong assumptions into downstream work.

• Current phase deliverables complete and accepted (per work acceptance criteria)
• Next phase inputs identified and available
• User approval obtained where required (e.g. deployment approval before Finalisation)

Common sequence: Setup → Research (optional) → Production (iterate until approved) → Learning (optional) → Finalisation.