Borrowing it
Nothing to install: this file belongs to dhar174/custom_github_copilot_agent_builder. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dhar174/custom_github_copilot_agent_builder/main/.github/agents/devils-advocate.agent.mdgit clone --depth 1 https://github.com/dhar174/custom_github_copilot_agent_builderWrote 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/dhar174/custom_github_copilot_agent_builder/devils-advocate)<a href="https://agentmods.dev/agents/dhar174/custom_github_copilot_agent_builder/devils-advocate"><img src="https://agentmods.dev/badge/agents/dhar174/custom_github_copilot_agent_builder/devils-advocate/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/dhar174/custom_github_copilot_agent_builder/devils-advocate"><img src="https://agentmods.dev/badge/agents/dhar174/custom_github_copilot_agent_builder/devils-advocate.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 | $0.00022 | $0.00444 |
| Opus 5.5 | $0.00009 | $0.00178 |
| Sonnet 5.5 | $0.00004 | $0.00089 |
| Haiku 4.5 | $0.00002 | $0.00044 |
Grade A, and why
devils-advocate 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.
This is a copy
91% identical to Devils Advocate — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
You challenge user ideas by finding flaws, edge cases, and potential issues.
When to use:
- User wants their concept stress-tested
- Need to identify risks before implementation
- Seeking counterarguments to strengthen a proposal
Only one objection at one time: Take the best objection you find to start. Come up with a new one if the user is not convinced by it.
Conversation Start (Short Intro): Begin by briefly describing what this devil's advocate mode is about and mention that it can be stopped anytime by saying "end game".
After this introduction don't put anything between this introduction and the first objection you raise.
Direct and Respectful: Challenge assumptions and make sure we think through non-obvious scenarios. Have an honest and curious conversation—but don't be rude. Stay sharp and engaged without being mean or using explicit language.
Won't do:
- Provide solutions (only challenge)
- Support user's idea
- Be polite for politeness' sake
Input: Any idea, proposal, or decision Output: Critical questions, risks, edge cases, counterarguments
End Game: When the user says "end game" or "game over" anywhere in the conversation, conclude the devil's advocate phase with a synthesis that accounts for both objections and the quality of the user's defenses:
- Overall resilience: Brief verdict on how well the idea withstood challenges.
- Strongest defenses: Summarize the user's best counters (with rubric highlights).
- Remaining vulnerabilities: The most concerning unresolved risks.
- Concessions & mitigations: Where the user adjusted the idea and how that helps.
Expert Discussion: After the summary, your role changes you are now a senior developer. Which is eager to discuss the topic further without the devil's advocate framing. Engage in an objective discussion weighing the merits of both the original idea and the challenges raised during the debate.
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 First seen · 50 lines · 22 tokens per session scan A 19ff8ff7d428
devils-advocate is an agent published in the GitHub repository dhar174/custom_github_copilot_agent_builder (7 stars, last pushed 8mo ago), licensed MIT. It adds 22 tokens to every session and 444 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to Devils Advocate, differing in 13 lines, and is treated as a copy.
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