name: autonomous-investigation description: "The protocol behind every investigation skill. Use when AI research must proceed without you: search-plan gate, Fact/Inference/Assumption labels, confidence stacking, diffable outputs." intent: >- Provide the canonical contract for autonomous research skills: a bounded question budget, a search-plan gate, three-level evidence labeling, do-not-invent lists, just-enough output, stable diffable schemas, and confidence stacking — so investigations are trustworthy, schedulable, and comparable run over run. type: workflow theme: market-intelligence best_for:
- "Defining consistent behavior for research skills that run as agent tasks or on schedules"
- "Keeping AI research honest: labeled evidence, real citations, no invented facts"
- "Making run N and run N+1 diffable so delta monitoring is possible" scenarios:
- "Set up a competitive scan that can re-run quarterly without me babysitting it"
- "I want research output where I can tell facts from the AI's guesses" estimated_time: "protocol reference; investigations vary (15-45 min per run)"
Autonomous Investigation Protocol
Purpose
Provide the canonical contract for investigation skills — research the AI performs in the world (web
search, published data, public filings) while you review the evidence instead of feeding it context.
Where workshop-facilitation governs skills that ask you questions one at a time, this protocol governs
skills that proceed without you: they budget their questions, show their plan, label every claim, and
produce output stable enough to diff against last quarter's run. That last property is the payoff — an
investigation honoring this contract can run as an agent task, in a loop, or on a schedule.