hanlons-razor

hanlons-razor is a skill for Claude Code, Codex from deciqAI/knowledge-skills. It costs 110 tokens per session (1,618 once invoked), scanned A, original, MIT.

A reasoning rule that says to test mistakes, misunderstanding, or missing information before assuming someone acted maliciously. It is a starting assumption, not proof that bad intent is absent.

In plain words
What is it for?
Use it during workplace disputes, partnership conflicts, surprising business moves, or harmful software output when intent is unclear.
Why use it?
It reduces unnecessary conflict and escalation when ordinary errors explain the evidence better than deliberate harm.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it during workplace disputes, partnership conflicts, surprising business moves, or harmful software output when intent is unclear.

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Install with agentmods
npx agentmods add skills/deciqai/knowledge-skills/hanlons-razor
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 deciqAI/knowledge-skills --skill hanlons-razor
Clone the repo
git clone --depth 1 https://github.com/deciqAI/knowledge-skills

Made for: Claude Code, Codex.

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 hanlons-razor

README.md
[![agentmods](https://agentmods.dev/badge/skills/deciqai/knowledge-skills/hanlons-razor/github.svg)](https://agentmods.dev/skills/deciqai/knowledge-skills/hanlons-razor)
Your own site
<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/hanlons-razor"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/hanlons-razor/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 hanlons-razor

Your own site · 80×15
<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/hanlons-razor"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/hanlons-razor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 110 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,618 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00110 $0.01618
Opus 5 $0.00055 $0.00809
Sonnet 5 $0.00022 $0.00324
Haiku 4.5 $0.00011 $0.00162

Measured 9d ago against content hash bcb414c96634, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

hanlons-razor 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.

hanlons-razor/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Hanlon's Razor

Overview

Before assuming someone hurt you on purpose, construct the version where they made a mistake — and see how much evidence it explains. The razor is a Bayesian prior, not a proof; override it when concrete evidence of malice arrives. Human attribution systematically over-weights intent (fundamental attribution error); most hostile-seeming acts are incompetence, miscommunication, or asymmetric information.

Composes with bayesian-reasoning, abductive-reasoning, occams-razor, critical-thinking.

When to Use

  • You feel an emotional pull toward "they did this on purpose"
  • You're about to escalate on the assumption of malice
  • A pattern of bad outcomes is being framed as a coordinated attack
  • A team is in conflict and each side believes the other is acting in bad faith
  • An AI model's harmful/biased output or a competitor's surprising AI move is being read as deliberate malice rather than an emergent bug, honest error, or ordinary self-interested competition

Not when: concrete evidence of malicious intent exists; cost of being wrong is catastrophic; power imbalance makes "they probably didn't mean it" an abuse-enabling stance.

Coaching Novices (Adaptive Front Door)

  • Engine mode: user has a concrete case → run The Process directly.
  • Coach mode: user is unfamiliar → guide step by step.

In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.

  1. One-line: before believing someone did it on purpose, construct the mistake version — see how much evidence it covers.
  2. Check fit: concrete malice evidence / catastrophic cost of being wrong → not this lens.
  3. Elicit the specific incident — what exactly happened?

[WAIT — do not advance until user responds]

  1. Work through The Process one step at a time with their input.

[WAIT — do not advance until user responds]

  1. Close: name the clarifying-conversation move + the override signal to watch for.

[WAIT — do not advance until user responds]

Read the full file on GitHub · 124 lines

Files

What ships with it

3 files 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 · 124 lines · 110 tokens per session scan A bcb414c96634

Subscribe to this mod's changes

hanlons-razor is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 110 tokens to every session and 1,618 once invoked, about $0.0006 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 2026-09-03.

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