challenge

A self-critique workflow that examines your existing notes about a belief or decision and builds an evidence-based case against it. It searches a personal knowledge vault for related writing and actions.

In plain words
What is it for?
Use it to test decisions such as career directions, technology choices, or business plans against evidence in your journal, projects, and reference notes.
Why use it?
It helps expose weak assumptions and confirmation bias—the tendency to notice evidence that supports what you already think. The result is a structured challenge to your current position.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/railly/agent-brain/challenge
Any agent
npx skills add Railly/agent-brain --skill challenge
Clone the repo
git clone --depth 1 https://github.com/Railly/agent-brain

Made for: Claude Code, Codex.

Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,293 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
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 $0.00016 $0.01293
Opus 5 $0.00008 $0.00647
Sonnet 5 $0.00003 $0.00259
Haiku 4.5 $0.00002 $0.00129

Measured 2d ago against content hash 7b291a928291, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

challenge scanned grade B with 1 finding 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 2d 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.

Strips warnings and disclaimersmediumAnti-refusal

Omitting safety caveats hides risk from the user and is a common jailbreak preamble.

- Don't lecture about "both sides", take a clear position in the verdict
.agents/skills/challenge/SKILL.md · 171 lines

How it starts

The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Read your current thinking on a topic and argue against it. Anti-sycophancy engine.

Usage: /challenge {topic or belief}

Examples:

  • /challenge YC is the right path for my startup
  • /challenge I should focus on Rust
  • /challenge v0 templates are worth my time
  • /challenge I need to learn math for ML
  • /challenge this is the best long-term career move

WAVE 0: Understand the Belief (PARALLEL)

# Tool Call Purpose
1 Grep Search $ARGUMENTS keywords across 03_Garden/concepts/, 02_Journal/daily/, 04_Projects/ Direct mentions in vault
2 Grep Search $ARGUMENTS keywords in 05_Areas/ Area-specific context
3 Read CLAUDE.md Goals and priorities context
4 Grep Search $ARGUMENTS keywords in 02_Journal/weekly/ Weekly goal history

WAVE 1: Map the Belief

Synthesize what you currently believe about this topic:

YOUR POSITION (as I understand it)
Topic: "{topic}"

Current stance:
{What you've written/done that supports this belief}

Evidence from your vault:
1. [{date}] {daily/note}: "{relevant quote or action}"
2. [{date}] {daily/note}: "{relevant quote or action}"
3. [{date}] {daily/note}: "{relevant quote or action}"

Strength of conviction: {HIGH/MEDIUM/LOW}
(based on: frequency of mentions, actions taken, resources invested)

Present this first. "Is this an accurate read of your position?"

If you correct it, I'll adjust before proceeding.

WAVE 2: Build the Counter-Case

Construct the strongest possible argument AGAINST the belief. Use these lenses:

Lens 1: Opportunity Cost

What are you NOT doing because of this belief?

OPPORTUNITY COST
By pursuing {belief}, you're implicitly deprioritizing:
- {thing 1} (evidence: {n} days since last engagement)
- {thing 2} (was in goals but dropped)
Time invested: ~{hours/weeks} based on commit/note frequency
What if that time went to {alternative}?

Lens 2: Survivorship Bias

Are you cherry-picking evidence?

SURVIVORSHIP BIAS
You remember: {the wins, the positive signals}
You might be ignoring:
- {failed attempt from vault}
- {abandoned related project}
- {negative signal you noted but didn't act on}

Read the full file on GitHub · 171 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.

  1. 2d ago First seen · 171 lines · 16 tokens per session scan B 7b291a928291

Subscribe to this mod's changes

challenge is a skill published in the GitHub repository Railly/agent-brain (22 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 1,293 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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