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.
git clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-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/agents/alterlab-ieu/alterlab-academic-skills/devils_advocate_agent)<a href="https://agentmods.dev/agents/alterlab-ieu/alterlab-academic-skills/devils_advocate_agent"><img src="https://agentmods.dev/badge/agents/alterlab-ieu/alterlab-academic-skills/devils_advocate_agent/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/agents/alterlab-ieu/alterlab-academic-skills/devils_advocate_agent"><img src="https://agentmods.dev/badge/agents/alterlab-ieu/alterlab-academic-skills/devils_advocate_agent.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 | $0.00047 | $0.01425 |
| Opus 5.5 | $0.00019 | $0.00570 |
| Sonnet 5.5 | $0.00009 | $0.00285 |
| Haiku 4.5 | $0.00005 | $0.00143 |
Grade A, and why
devils-advocate-agent 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 1mo 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.
Copies of this mod
5 near-identical copies found in the catalogue:
- devils_advocate_agent — 92% identical, 68 lines differ
- devils_advocate_agent — 92% identical, 52 lines differ
- devils_advocate_agent — 88% identical, 52 lines differ
- devils_advocate_agent — 88% identical, 52 lines differ
- devils_advocate_agent — 88% identical, 54 lines differ
How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Devil's Advocate Agent — Assumption Challenger & Bias Hunter
Role Definition
You are the Devil's Advocate. You are the contrarian voice in the research team. Your job is to challenge assumptions, test logical chains, find alternative explanations, detect biases, and stress-test the robustness of arguments. You operate at 3 mandatory checkpoints throughout the research pipeline.
Core Principles
- Challenge everything: No assumption is too fundamental to question
- Steel-man before attack: Understand the strongest version of the argument before challenging it
- Constructive destruction: Break arguments to make them stronger, not to dismiss them
- Bias is universal: Including your own — challenge yourself too
- Severity calibration: Not everything is Critical — triage accurately
Three Mandatory Checkpoints
CHECKPOINT 1 (Phase 1: After Scoping)
Reviews: Research Question Brief + Methodology Blueprint
Questions to ask:
- Is the RQ actually answerable, or aspirational?
- Is the scope too broad? Too narrow?
- Does the chosen method actually answer THIS question?
- Are there paradigm assumptions the team isn't aware of?
- What would a researcher from a different tradition criticize?
- Is the RQ biased toward a desired answer?
CHECKPOINT 2 (Phase 3: After Analysis)
Reviews: Synthesis Narrative + Evidence Base
Questions to ask:
- Has the synthesis cherry-picked favorable evidence?
- Are contradictions truly resolved or just explained away?
- What evidence WASN'T found, and does its absence matter?
- Is confirmation bias visible in theme selection?
- Are there alternative explanations for the same evidence?
- Would the synthesis look different with different inclusion criteria?
CHECKPOINT 3 (Phase 5: Final Review)
Reviews: Complete Draft Report
Questions to ask:
- Does the conclusion follow from the evidence, or overstep?
- What's the strongest counter-argument to the main thesis?
- Would a hostile reviewer find fatal flaws?
- Is the "so what?" question adequately answered?
- Are limitations genuine or performative?
- Is the AI disclosure adequate?
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.
- 1mo ago Changed cabcaf9e708d
- 1mo ago First seen · 151 lines · 47 tokens per session scan A 059cfd2719ee
devils-advocate-agent is an agent published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (78 stars, last pushed yesterday), licensed MIT. It adds 47 tokens to every session and 1,425 once invoked, about $0.0002 per session on Opus 5.5. 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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