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Automation
Command

/probe

8 personas interrogate requirements until constraints saturate

From plugin
autoresearch
5.8k14 skills14 commands
Install
> /plugin marketplace add uditgoenka/autoresearch
> /plugin install autoresearch@autoresearch

How it fires

How this command gets triggered: by you, by Claude, or both.

  • Fires itselfClaude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/probe

Context preview

What this command does when you run it.

8 personas interrogate requirements until constraints saturate

Command definition

probe.md
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]"

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. Propagate --evals flag.

Read more
Ships withautoresearch

Turn Claude Code, OpenCode, or OpenAI Codex into a relentless improvement engine. Based on Karpathy's autoresearch — constraint + mechanical metric + autonomous iteration = compounding gains.

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Repo: uditgoenka/autoresearch