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.
npx skills add digital-stoic-org/agent-skills --skill challengegit clone --depth 1 https://github.com/digital-stoic-org/agent-skillsWrote 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.
[](https://agentmods.dev/skills/digital-stoic-org/agent-skills/challenge)<a href="https://agentmods.dev/skills/digital-stoic-org/agent-skills/challenge"><img src="https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/challenge/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.
<a href="https://agentmods.dev/skills/digital-stoic-org/agent-skills/challenge"><img src="https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/challenge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00132 | $0.01018 |
| Opus 5 | $0.00066 | $0.00509 |
| Sonnet 5 | $0.00026 | $0.00204 |
| Haiku 4.5 | $0.00013 | $0.00102 |
Grade A, and why
challenge 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.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Challenge
Apply structured provocation patterns to force reconsideration of current work or upcoming intentions.
Target: $ARGUMENTS
Critical constraint
The interviewer (this skill, running in the main conversation) DELIVERS the queue. It NEVER
regenerates findings in the main context. Regenerating brings anchoring back through the side
door and destroys the benefit of the fresh-context generator. All finding generation happens in
deep's sub-agent or, for forward/anchor/verify/framing, in the protocol execution itself
— never re-derived afterward from parent-conversation reasoning.
Dispatch
Parse first word of $ARGUMENTS as subcommand. No recognized subcommand → route.
| Subcommand | Generator | Delivery | Protocol |
|---|---|---|---|
route (default) |
none | ≤5 lines, 0 sub-agent | Read protocols/route.md → execute |
forward |
main context, 5 patterns | interactive walk | Read protocols/forward.md → execute |
anchor |
main context, 4 patterns | interactive walk | Read protocols/anchor.md → execute |
verify |
main context, 3 patterns | interactive walk | Read protocols/verify.md → execute |
framing |
main context, 2 patterns | interactive walk | Read protocols/framing.md → execute |
deep |
fresh sub-agent, 9 patterns | interactive walk, top-N | see below |
deep --report |
fresh sub-agent, 9 patterns | batch report (legacy escape hatch) | see below |
/challenge <free-text description> with no matching subcommand keyword is route, not an error
and not a menu — route is the default entry point.
Deep Subcommand
Spawn ONE sub-agent via the Agent tool:
- subagent_type:
dstoic:devil-advocate:devil-advocate - prompt: target description + relevant file paths to read
- The agent executes all 9 patterns IN SEQUENCE (anchor: Gatekeeper, Reset, Alternative Approaches, Pre-mortem · verify: Proof Demand, CoVe, Fact Check List · framing: Socratic, Steelman) inside its own fresh context — not 9 parallel agents, one agent running 9 steps.
- It returns a structured queue (
reference.md§Queue Schema), not a batch report. - DO NOT pass parent conversation reasoning into the prompt — fresh context, uncontaminated by the anchoring already present in the main conversation, is the entire point.
What ships with it
6 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.
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.
- 9d ago First seen · 76 lines · 132 tokens per session scan A 5400c3b30415
challenge is a skill published in the GitHub repository digital-stoic-org/agent-skills (20 stars, last pushed 2d ago), licensed MIT. It adds 132 tokens to every session and 1,018 once invoked, about $0.0007 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.
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