autoresearch:predict

autoresearch:predict is a skill for Claude Code from wjgoarxiv/autoresearch-skill. It costs 99 tokens per session (2,200 once invoked), scanned A, original, MIT.

A structured forecasting process that gathers independent views from different roles, challenges those views, checks for group agreement, and produces a judge's summary with confidence levels.

In plain words
What is it for?
It helps analyse predictions, scenarios, and decisions through independent reasoning, cross-examination, rebuttals, anti-groupthink checks, and a final synthesis.
Why use it?
It reduces the chance that one early opinion or a group consensus hides important disagreement.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the autoresearch plugin — 13 skills shipped together

Good fit It helps analyse predictions, scenarios, and decisions through independent reasoning, cross-examination, rebuttals, anti-groupthink checks, and a final synthesis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wjgoarxiv/autoresearch-skill/predict
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.

Any agent
npx skills add wjgoarxiv/autoresearch-skill --skill predict
Clone the repo
git clone --depth 1 https://github.com/wjgoarxiv/autoresearch-skill

Made for: Claude Code.

Or install autoresearch, the plugin that ships this one along with the rest of its 13 skills.

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.

agentmods badge for autoresearch:predict

README.md
[![agentmods](https://agentmods.dev/badge/skills/wjgoarxiv/autoresearch-skill/predict/github.svg)](https://agentmods.dev/skills/wjgoarxiv/autoresearch-skill/predict)
Your own site
<a href="https://agentmods.dev/skills/wjgoarxiv/autoresearch-skill/predict"><img src="https://agentmods.dev/badge/skills/wjgoarxiv/autoresearch-skill/predict/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.

agentmods 80×15 button for autoresearch:predict

Your own site · 80×15
<a href="https://agentmods.dev/skills/wjgoarxiv/autoresearch-skill/predict"><img src="https://agentmods.dev/badge/skills/wjgoarxiv/autoresearch-skill/predict.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,200 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 original No closer match found 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00099 $0.02200
Opus 5 $0.00049 $0.01100
Sonnet 5 $0.00020 $0.00440
Haiku 4.5 $0.00010 $0.00220

Measured 9d ago against content hash f8fc62fec8a0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

autoresearch:predict 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 9d 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.

skills/predict/SKILL.md · 260 lines

How it starts

The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Predict: Multi-Perspective Deliberation Engine

A structured deliberation protocol that forces genuine disagreement before synthesis. Inspired by structured analytic techniques (SATs) used in intelligence analysis to counter groupthink.

Autonomy Directive

You are an autonomous deliberation agent. Once the deliberation begins:

  1. NEVER STOP between phases to ask for permission.
  2. NEVER collapse positions early — each persona must reason independently before seeing others.
  3. NEVER let the judge synthesize before all rounds are complete.
  4. Run all 8 phases sequentially without interruption. The user may have walked away.

The 8-Phase Deliberation Protocol

[Question] --> [Frame] --> [Personas] --> [Independent Positions]
    --> [Position Summary] --> [Cross-Examination] --> [Rebuttal]
    --> [Anti-Herd Detection] --> [Judge Synthesis] --> [predict-report.md]

Phase 1 — Frame the Question Precisely

Before any persona speaks, the agent must sharpen the question:

  • Restate the question in unambiguous terms. Remove vagueness.
  • Identify the decision horizon (short-term? 5 years? upon release?).
  • Define measurable outcomes where possible ("will X exceed Y by date Z").
  • List what the question does NOT include (scope boundaries).
  • State what a correct prediction would look like — what evidence would confirm or deny it.

Log the framed question to predict-report.md under ## Framed Question.


Phase 2 — Enumerate Personas

Select 4–6 personas from persona-templates.md based on the question domain.

Selection rules:

  • Always include at least one Optimist and one Pessimist for baseline polarity.
  • Always include at least one domain Expert for technical grounding.
  • For decisions with tail risks, add the Black Swan Hunter.
  • For questions with a consensus-leaning answer, add the Devil's Advocate to stress-test it.
  • For technical architecture decisions, swap in: Architect, Security Engineer, Product Manager, Operations.

Read the full file on GitHub · 260 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

  1. 9d ago First seen · 260 lines · 99 tokens per session scan A f8fc62fec8a0

Subscribe to this mod's changes

autoresearch:predict is a skill published in the GitHub repository wjgoarxiv/autoresearch-skill (32 stars, last pushed 2mo ago), licensed MIT. It adds 99 tokens to every session and 2,200 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens