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ariffazil

Chain Reason

by ariffazil · GitHub ↗ · v1.0.3 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install chain-reason
Description
Provides detailed, auditable multi-step reasoning traces for complex questions requiring 3+ logical steps, tradeoff analysis, or explicit explanation requests.
README (SKILL.md)

Chain Reason — Explicit Reasoning Traces

arifOS constitutional floors demand auditability. For complex reasoning, show the work.

When to Use Chain Reason

  • Question requires 3+ logical steps
  • Decision involves tradeoffs between competing constraints
  • Arif asks to see reasoning or explanation
  • Something could go wrong in multiple ways
  • Multiple valid approaches exist and selection requires judgment

The 5-Step Trace Format

CHAIN REASONING:
1. [GIVEN]  → What is known/established
2. [CONSTRAINT] → What must be satisfied
3. [APPROACH] → How to get from given to solution
4. [STEP-N] → Intermediate steps (numbered)
5. [CONCLUSION] → Final answer with confidence

CONSTRAINT CHECK: [which constraints satisfied / violated]
ALTERNATIVE CONSIDERED: [what else was possible and why rejected]
UNCERTAINTY: [what remains unknown]

Example Trace

Question: "Should I deploy arifOS MCP to production now?"

CHAIN REASONING:
1. [GIVEN]   → Current vitality 0.82, version 2026.04.11+, nginx proxy configured
2. [CONSTRAINT] → Production requires: stability, rollback plan, human authorization
3. [APPROACH] → Evaluate readiness against deployment checklist
4. [STEP-1]  → Vitality > 0.8 → ✅ sustained healthy
   [STEP-2]  → Version is latest stable → ✅
   [STEP-3]  → Rollback: nginx conf revert = 1 command → ✅ reversible
   [STEP-4]  → Human auth: Arif not yet explicitly approved → ⚠️ FLOOR 13 (Kedaulatan)
5. [CONCLUSION] → Technical readiness: ✅ | Authorization: ❌ → HOLD

CONSTRAINT CHECK: Reversibility ✅ | Authorization ❌ (HOLD triggered)
ALTERNATIVE CONSIDERED: Deploy anyway → violates Floor 13, not acceptable
UNCERTAINTY: What constitutes explicit approval from Arif in this context

Tradeoff Weighing Format

For decisions with competing goods:

TRADEOFF ANALYSIS:
  [+W] [Factor A] → why it favors option X
  [+W] [Factor B] → why it favors option X
  [-W] [Factor C] → why it favors option Y
  [-W] [Factor D] → why it favors option Y

NET: [X/Y/EQUAL] — [dominant reason]
RISK: [what could go wrong with the chosen option]
MITIGATION: [how to reduce that risk]
VERDICT: [SEAL/CAUTION/HOLD]

Epistemic Trace (for knowledge questions)

EVIDENCE CHAIN:
  [1] OBS: \x3Cdirect observation or fact>
  [2] DER: \x3Cderived from above>
  [3] INT: \x3Cinterpretation (label as such)>
  [4] SPEC: \x3Cspeculation (label as such)>

CONFIDENCE: [HIGH/MEDIUM/LOW] — [reason]
GAP: [what evidence is missing]

Rules

  1. Number every step — enables traceable audit
  2. Label assumptions — don't silently assume, state explicitly
  3. Show alternatives — why this approach and not another
  4. End with a verdict — SEAL / CAUTION / HOLD / VOID
  5. Keep it tight — if the trace exceeds 20 steps, the problem is not yet decomposed enough
Usage Guidance
This skill is coherent for its stated purpose — it simply prescribes how the agent should present multi-step reasoning. Before installing, decide whether you want the agent to emit explicit chain-of-thought traces: those outputs can reveal intermediate reasoning steps and heuristics that you may prefer not to expose (to users, logs, or external systems). Also note the keyword triggers are broad and may cause the skill to activate more often than you expect. If concerned, test in a sandbox, restrict who can invoke the skill, or ask the skill author to narrow triggers (or require an explicit opt-in token) and to include guardrails about omitting sensitive internal heuristics from traces.
Capability Analysis
Type: OpenClaw Skill Name: chain-reason Version: 1.0.3 The skill bundle contains only metadata and markdown instructions (SKILL.md) designed to guide an AI agent's reasoning process using structured templates. There is no executable code, no network activity, and no instructions that attempt to exfiltrate data or bypass security controls.
Capability Assessment
Purpose & Capability
Name/description promise an explicit reasoning-trace formatter and the SKILL.md contains only templates, rules, and activation guidance for when to emit traces. There are no unrelated env vars, binaries, or install steps requested.
Instruction Scope
The runtime instructions are limited to producing formatted traces and tradeoff analyses and do not direct file I/O, network calls, or credential access. Note: the skill uses keyword triggers (e.g., 'reason', 'how', 'why') which are broad and can cause frequent activation; it also deliberately exposes chain-of-thought style outputs, which may leak internal reasoning if you consider that sensitive.
Install Mechanism
Instruction-only skill with no install spec and no code files; nothing is written to disk and no external packages are downloaded.
Credentials
No environment variables, credentials, or config paths are requested. The SKILL.md does not reference undeclared secrets or external services.
Persistence & Privilege
Skill does not request always:true or system-level persistence. Default autonomous invocation is allowed by platform but the skill itself does not escalate privileges or modify other skills.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install chain-reason
  3. After installation, invoke the skill by name or use /chain-reason
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.3
Third retry - version 1.0.3
v2.0.0
Initial release: explicit multi-step reasoning traces
v1.0.2
Initial release: explicit multi-step reasoning traces
v1.0.1
Initial release: explicit multi-step reasoning traces
v1.0.0
Initial release: explicit multi-step reasoning traces
Metadata
Slug chain-reason
Version 1.0.3
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 5
Frequently Asked Questions

What is Chain Reason?

Provides detailed, auditable multi-step reasoning traces for complex questions requiring 3+ logical steps, tradeoff analysis, or explicit explanation requests. It is an AI Agent Skill for Claude Code / OpenClaw, with 136 downloads so far.

How do I install Chain Reason?

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

Is Chain Reason free?

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

Which platforms does Chain Reason support?

Chain Reason is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Chain Reason?

It is built and maintained by ariffazil (@ariffazil); the current version is v1.0.3.

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