What is autoresearch_probe?

A requirements-questioning workflow that uses several viewpoints to examine a feature, requirement, or design until few new constraints are found. A constraint is a condition the solution must satisfy.

Use it to interrogate a topic interactively, where you answer questions, or autonomously, where answers are inferred from the codebase. It can focus on selected files and use adversarial viewpoints to challenge the proposal.

It helps uncover missing requirements, assumptions, and boundary conditions before work begins. This reduces the chance of designing around an incomplete understanding of the problem.

autoresearch_probe — Command for Claude Code and OpenCode by WdBlink

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo

git clone --depth 1 https://github.com/WdBlink/autoresearch-paper

Made for: Claude Code, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/commands/wdblink/autoresearch-paper/autoresearch_probe/github.svg)](https://agentmods.dev/commands/wdblink/autoresearch-paper/autoresearch_probe)

Your own site

<a href="https://agentmods.dev/commands/wdblink/autoresearch-paper/autoresearch_probe"><img src="https://agentmods.dev/badge/commands/wdblink/autoresearch-paper/autoresearch_probe/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/commands/wdblink/autoresearch-paper/autoresearch_probe"><img src="https://agentmods.dev/badge/commands/wdblink/autoresearch-paper/autoresearch_probe.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 1,230 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 97% copy Near-identical to another mod in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00013	$0.01230
Opus 5.5	$0.00005	$0.00492
Sonnet 5.5	$0.00003	$0.00246
Haiku 4.5	$0.00001	$0.00123

Measured 3d ago against content hash 830f96ff30ec, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

autoresearch_probe scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

97% identical to autoresearch:probe — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.opencode/commands/autoresearch_probe.md · 118 lines

How it starts

The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 question) 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)

question (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

Read the full file on GitHub · 118 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

3d ago First seen · 118 lines · 13 tokens per session scan A 830f96ff30ec

Subscribe to this mod's changes

autoresearch_probe is a command published in the GitHub repository WdBlink/autoresearch-paper (2 stars, last pushed 4d ago), licensed MIT. It adds 13 tokens to every session and 1,230 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to autoresearch:probe, differing in 8 lines, and is treated as a copy.

Planning Research academic-writing agent-skills ai ai-agents autonomous-research

autoresearch_probe next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
autoresearch_probeWdBlink/autoresearch-paper	Command	2	4d ago	MIT	A	13	Claude Code, OpenCode
ars-planImbad0202/academic-research-skills	Command	56k	yesterday	none	A	19	Claude Code
ars-revision-coachImbad0202/academic-research-skills-codex	Command	14k	5d ago	none	A	27	Claude Code
ars-3wImbad0202/academic-research-skills-codex	Command	14k	5d ago	none	A	24	Claude Code
nextProjectDXAI/labrat	Command	237	3mo ago	MIT	A	0	Claude Code
ja-fallbackZaious/journal-atlas	Command	2	10d ago	none	A	37	Claude Code
ai-reviewStill-chowline394/MagicTeX-mcp	Command	0	1mo ago	AGPL-3.0	A	13	Claude Code