Autonomous Investigation by @deanpeters · Skillet

deanpeters@deanpeters

Autonomous Investigation

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.

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autonomous-investigation

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.

Input

Nothing required — this skill defines the protocol other investigation skills follow. Also useful when invoked standalone: the target of the investigation and, above all, the decision the research should support. Research without a decision is a hobby; every investigation skill asks for the decision because it determines what "just enough" means.

Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it, credit it against the question budget, and don't re-ask.

Arriving empty-handed? That works too. The protocol's whole design is to proceed on best-available evidence with labeled assumptions when nobody answers questions. When another skill references this protocol, that skill's Input section governs what to provide.

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	`workshop-facilitation`	`autonomous-investigation`
Who holds the context	The user	The world (public sources)
Interaction shape	One question per turn	Question budget, then proceed
Blocked by silence?	Yes — waits for answers	No — labels assumptions and continues
Schedulable?	No	Yes — that's the point

Question budget — a hard cap (usually 3) on clarifying questions. When the budget is spent or nobody answers, proceed with labeled assumptions. This is what makes investigations schedulable: an unattended run degrades gracefully instead of stalling.
Search-plan gate — before researching, show a 3-bullet plan: what you'll search, which source types, how you'll separate fact from inference. Continue unless the user revises it. Why it teaches: reviewing a plan takes 10 seconds; reviewing a wrong report takes 10 minutes. The gate is the cheapest correction point in the whole workflow.
Evidence labels — every key claim carries exactly one label:
- Fact — source-supported; a checkable URL sits next to it
- Inference — evidence-based interpretation; the evidence is cited, the leap is yours to judge
- Assumption — working guess made to keep moving; listed for validation Keep labels short. Things you couldn't find are not a fourth label — they go in an explicit gaps list. Why it teaches: most competitive "facts" in strategy decks are unlabeled inference. Three-level honesty is the habit that separates intelligence from confident storytelling.
Do-not-invent list — each investigation skill names its domain's specific fabrication risks (competitors, pricing, market share, patent contents, customer wins...) and forbids inventing them. Real, checkable URLs only; a claim without a source and date is an opinion wearing a badge. Why it teaches: the list tells the human exactly what to verify first.
Just Enough Mode — default output is the strongest findings in short bullets, sized to the decision. Verbose Mode exists only on request. Research value is decision support, not page count.
Stable output schema — section order and structure never drift between runs, so run N and run N+1 are diffable. Delta monitoring, scheduled refreshes, and "what changed since last quarter" all depend on this clause.
Final Step block — end with exactly 4 numbered next options (artifacts to build, deeper passes to run, assumptions to validate). Accept 1, 1 and 3, Verbose Mode, or a custom path.

1 channel flags it   → Watch item. Log it, do nothing.
2 channels agree     → Working hypothesis. Assign someone to probe.
3+ channels agree    → Actionable intelligence. Brief leadership, adjust plans.
Channels conflict    → The most interesting case. Someone is bluffing. Dig.