Contract

For each sub-agent you plan to dispatch, define a schema before the call:

• goal — one-sentence objective
• inputs — data/context the sub-agent receives
• artifacts — named structured fields expected back (not freeform prose)
• non_goals — what the sub-agent must NOT do
• failure_modes — how to report blocked or partial work
• domain (optional) — the knowledge domain for this task. Guides how research, specification, and verification adapt. Common values: software, research, design, business — but any freeform string works (e.g., healthcare, legal, education). When omitted, infer from context: git repo present → software; PDFs/papers/citations in working directory → research; design files/brand assets → design; financial models/strategy docs → business. Default fallback: software.

Embed the schema at the top of every sub-agent's prompt and require results in that exact shape. Instruct each sub-agent explicitly: "Return ONLY the schema fields. No preamble, no analysis prose, no explanation — begin your response with the first schema field." When sub-agents return, validate field-by-field. If any artifact is missing, malformed, or wrapped in prose, re-dispatch only the failing sub-agent with the gap cited. Merge only schema-valid responses.

Also instruct each sub-agent to stop on non-convergence: if repeated attempts at the same sub-goal stop making progress after a few tries, do not keep retrying — return the best partial result through the schema's designated failure/partial channel (failure_modes, or whatever blocked/unverified field that agent's schema defines), naming what could not be resolved. Activity is not progress.

Epistemic confidence

Recommended for all sub-agents. Add to your return schema:

• confidence — low / medium / high — how confident is the sub-agent in the completeness and accuracy of its findings?
• coverage_gaps — what the sub-agent couldn't access, verify, or search (e.g., proprietary databases, paywalled sources, unpublished practitioner knowledge, subjective judgment areas)
• boundary_flag — if the sub-agent hit an epistemic boundary, name it: non-falsifiable (claim can't be tested), low-coverage (search was limited), tacit-knowledge (unwritten knowledge required), unprecedented (genuinely novel, no baseline), time-sensitive (answer depends on current state), or none
• recommended_action — what should happen next: proceed (findings solid, move ahead), human-gate (pause for human judgment before acting), re-retrieve (try different search strategy or sources), elicit (generate prompts to validate with domain experts)

This is NOT required — skills that don't return it continue to work. But when present, coverage gaps and boundary flags surface automatically during merge, preventing silent failures.

Skip if

• Single-agent dispatch
• Sub-agents returning freeform prose where structure doesn't help merge
• Exploratory tasks where the output shape isn't known yet