/probe

name: autoresearch:probe
description: "8 personas interrogate requirements until constraints saturate"
argument-hint: "[Topic: <text>] [Scope: <glob>] [--depth shallow|standard|deep] [--personas N] [--mode interactive|autonomous] [Iterations: N] [--evals]"
disable-model-invocation: true

EXECUTE IMMEDIATELY.

Parse Arguments

Extract from $ARGUMENTS:

• `Topic:` — strip keyword, remaining text is topic (or full $ARGUMENTS if no keyword)
• `Scope:` or `--scope` — file globs for codebase grounding
• `Depth:` or `--depth` — shallow (5 rounds), standard (15), deep (30)
• `--personas N` or `Personas:` — active persona count (3-8, default 6)
• `--saturation-threshold N` — net-new constraints/round below which counts toward saturation (default 2)
• `--mode` or `Mode:` — interactive (default, uses AskUserQuestion) or autonomous (self-answers from codebase)
• `--adversarial` — rotate hostile personas to front
• `Iterations:` or `--iterations` — default 15 rounds. "unlimited" for unbounded.
• `--evals`, `--evals-interval N`, `--chain`, `--<subcommand>`

Setup (if Topic missing)

AskUserQuestion (single batch): Q1 (Topic): "What to probe?" — open text describing feature, requirement, or design Q2 (Scope): "Which files for context?" — suggested globs + entire codebase Q3 (Depth): "How deep?" — shallow (5 rounds), standard (15), deep (30), unlimited Q4 (Mode): "How to answer persona questions?" — interactive (you answer), autonomous (agent infers from code) If all provided → skip.

8 Personas

| # | Persona | Focus | |---|---|---| | 1 | Domain Expert | Business rules, domain constraints, terminology | | 2 | End User | Usability, expectations, error recovery | | 3 | Skeptic | Assumptions that might be wrong | | 4 | Edge-Case Hunter | Boundary conditions, rare scenarios | | 5 | Ops Engineer | Deployment, monitoring, scaling, failure modes | | 6 | Security Reviewer | Attack vectors, data protection, auth | | 7 | Contradiction Finder | Conflicts between requirements | | 8 | Scope Guardian | Feature creep, unnecessary complexity |

If --adversarial: rotate Skeptic + Contradiction Finder + Edge-Case Hunter to front.

Phase 1: Seed

• Parse topic into initial constraint set
• Read codebase context (if --scope provided)
• Initialize constraint registry (empty)

Round Loop

Phase 2: Persona Activation

• Select 2-3 personas for this round (rotate through all 8)
• Each persona generates 3-5 probing questions from their perspective

Phase 3: Codebase Grounding

• Check questions against existing code for evidence
• Annotate questions with: relevant file:line, existing behavior, gaps

Phase 4: Answer Capture

• **Interactive mode:** present questions via AskUserQuestion, collect answers
• **Autonomous mode:** infer answers from codebase context, label confidence (high/medium/low)

Phase 5: Constraint Extraction

• Parse answers into atomic constraints
• Each constraint: id, source persona, description, confidence, evidence
• Deduplicate against existing registry

Phase 6: Cross-Check

• Check new constraints against existing for conflicts
• Flag contradictions for resolution (interactive → ask user, autonomous → note uncertainty)

Phase 7: Saturation Check

• Count net-new constraints this round
• If net-new < saturation_threshold for 3 consecutive rounds → SATURATED, exit loop
• Track: total constraints, new this round, saturation window

Phase 8: Log

Append to output: round number, personas active, questions asked, constraints extracted, net-new count

Eval Checkpoint

If --evals: check if current_round % interval == 0 → run checkpoint.

Bounded Check

If bounded: current_round >= max_iterations → exit loop.

Phase 9: Synthesize & Output

Create output directory: `autoresearch/probe-{YYMMDD}-{HHMM}/`

1. Write `constraints.md` — full constraint registry organized by category 2. Write `conflicts.md` — unresolved contradictions 3. Generate ready-to-run autoresearch config:

• Derived Goal, Scope, Metric, Verify from constraints
• Include as code block in summary.md

Print: total rounds, constraints found, saturation status, unresolved conflicts.

Summary

Print: total rounds, total constraints, net-new trend, saturation status, top 5 most impactful constraints.

Eval Checkpoint (--evals flag)

If --evals present:

• Compute interval: floor(max_iterations / 3), min 1. Fixed 10 if unbounded.
• Print: `--- Eval Checkpoint (rounds {X}-{Y}) ---\nConstraints: {total} (+{new}) | Saturation: {window_count}/3\n{recommendation}\n---`
• If saturated 3+ checkpoints → recommend early stop.
• At loop end → full evals summary to evals-summary.md.

Chain Handoff

Write handoff.json: version "2.1.0", source "probe", timestamp, status (COMPLETE|SATURATED|USER_INTERRUPT|BOUNDED|ERROR), findings = constraints, config = derived autoresearch config. Invoke next target in --chain order via the `autoresearch` skill's Subcommand routing. Propagate --evals flag.