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cwheeler67

Autoreason Lite

by Christopher Wheeler · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install autoreason-lite
Description
Apply a bounded multi-candidate self-refinement loop (A/B/AB + judges + do-nothing option) to improve drafts, plans, and analyses while preventing scope cree...
README (SKILL.md)

Autoreason Lite

Use this skill when a user asks to "improve this," "refine this," or "make this better" and quality matters more than one-shot speed.

What this does

A bounded refinement tournament:

  1. A (incumbent): current draft unchanged
  2. B (adversarial revision): deliberately different attempt
  3. AB (synthesis): merge best parts of A and B
  4. Judging pass: pick winner with explicit rubric
  5. Convergence rule: stop early if A keeps winning (no-change is valid)

This reduces over-editing and drift.

Default operating profile

  • Max rounds: 3
  • Judges: 3 independent judge personas
  • Aggregation: Borda-like ranking (1st=2 pts, 2nd=1 pt, 3rd=0)
  • Convergence: stop if A wins 2 rounds (or winner unchanged 2 rounds)
  • Length guardrail: output within ±15% of requested length unless user asks otherwise
  • Voice lock: preserve user's tone profile (technical / founder / viral) unless asked to shift

When to use

Use for:

  • Long-form writing
  • Strategy memos
  • Explanations/tutorial drafts
  • Product copy
  • Decision frameworks

Avoid for:

  • Deterministic factual extraction
  • Tiny edits user already specified exactly
  • Time-critical one-liners unless user requests deep refinement

Execution steps

  1. Clarify success criteria (tone, audience, length, goal) if missing.
  2. Generate candidate B from A:
    • Must change structure or argument order (not just wording).
    • Must preserve critical facts.
  3. Generate candidate AB:
    • Keep strongest parts from A and B.
    • Remove redundancy.
  4. Run 3 judges independently with rubric:
    • Accuracy / faithfulness
    • Clarity
    • Usefulness for user goal
    • Concision / scope control
  5. Score candidates; choose winner.
  6. Repeat up to max rounds with winner as new A.
  7. Return final with short “what changed + why”.

Judge prompt template

Use references/judge-rubric.md.

Output format to user

  • Final refined result
  • 2-4 bullets: key improvements
  • Optional: one-line note if loop stopped due to convergence (no meaningful gain)

Quick presets

  • Technical: precise wording, fewer claims, concrete mechanisms
  • Founder: outcomes + positioning + credibility signal
  • Viral: short lines, strong hooks, high readability, no fluff

Safety + quality constraints

  • Never invent facts to make prose sound better.
  • Keep user intent stable unless explicitly asked to pivot.
  • Prefer no-change over noisy edits.
  • If confidence drops, surface uncertainty instead of bluffing.
Usage Guidance
This skill appears coherent and low-risk: it only defines an internal editing workflow and does not request credentials or install code. Before installing, consider that (1) the judges are LLM personas (not external human auditors), so verify final outputs for factual accuracy and sensitive content, (2) if you will submit proprietary or confidential text, check your platform's data-logging/privacy policy since the skill will operate on user-provided content, and (3) if you need stricter guarantees (no autonomous invocation), confirm platform-level invocation controls.
Capability Analysis
Type: OpenClaw Skill Name: autoreason-lite Version: 1.0.0 The skill bundle provides a structured logic framework for an AI agent to perform iterative text refinement through a multi-candidate 'tournament' process. It contains only markdown instructions (SKILL.md) and a rubric (references/judge-rubric.md) with no executable code, network access, or file system operations. The instructions explicitly emphasize faithfulness to user intent and safety constraints, such as avoiding hallucinations.
Capability Assessment
Purpose & Capability
Name/description match the instructions: the skill describes a bounded multi-candidate refinement process for improving drafts and its steps and presets align with that goal.
Instruction Scope
SKILL.md only describes internal candidate-generation and judging steps, references a local rubric file, and does not instruct reading unrelated files, accessing environment variables, or sending data to external endpoints.
Install Mechanism
No install spec and no code files — nothing is written to disk or downloaded by the skill itself, which minimizes installation risk.
Credentials
The skill declares no required environment variables, credentials, or config paths; requested capabilities are proportional to an editing/refinement function.
Persistence & Privilege
always is false and there is no installation behavior that persists or modifies system/other-skill config. The skill can be invoked autonomously per platform defaults, which is expected for this type of skill.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install autoreason-lite
  3. After installation, invoke the skill by name or use /autoreason-lite
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: bounded A/B/AB refinement loop with judge rubric, convergence, tone presets
Metadata
Slug autoreason-lite
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Autoreason Lite?

Apply a bounded multi-candidate self-refinement loop (A/B/AB + judges + do-nothing option) to improve drafts, plans, and analyses while preventing scope cree... It is an AI Agent Skill for Claude Code / OpenClaw, with 81 downloads so far.

How do I install Autoreason Lite?

Run "/install autoreason-lite" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Autoreason Lite free?

Yes, Autoreason Lite is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Autoreason Lite support?

Autoreason Lite is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Autoreason Lite?

It is built and maintained by Christopher Wheeler (@cwheeler67); the current version is v1.0.0.

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