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 martineserios/thebrana --skill challengegit clone --depth 1 https://github.com/martineserios/thebranaWrote 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/martineserios/thebrana/challenge)<a href="https://agentmods.dev/skills/martineserios/thebrana/challenge"><img src="https://agentmods.dev/badge/skills/martineserios/thebrana/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/martineserios/thebrana/challenge"><img src="https://agentmods.dev/badge/skills/martineserios/thebrana/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 | $0.00026 | $0.06086 |
| Opus 5.5 | $0.00010 | $0.02434 |
| Sonnet 5.5 | $0.00005 | $0.01217 |
| Haiku 4.5 | $0.00003 | $0.00609 |
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 21d 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 — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Challenge
Adversarial review with two modes. Standard: three native challenger subagents (convergent · systems · critical) stress-test reasoning, Gemini retrieves documented constraints — all run independently, Claude merges and judges. Council (--council): Four parallel perspective agents (devil's advocate, optimist, pragmatist, operator) plus Gemini — Claude synthesizes across all five.
Deep (--deep, or auto on high-stakes): any mode, plus an adversarial verification stage — every merged finding is independently re-attacked by N skeptics (verify-findings workflow), so plausible-but-wrong findings are dropped to FALSE_POSITIVE and survivors get a calibrated severity before you see them. All agents are native subagents on the subscription — no ruflo, no API key.
-
Gather context about what to challenge:
- If
$ARGUMENTSprovided, use it as the description of what to challenge. - If
$ARGUMENTScontains--council: strip--councilfrom the target description, activate council mode — step 4a spawns 4 parallel perspective agents instead of one Opus agent. All other steps unchanged. - If
$ARGUMENTScontains--hats: strip--hatsfrom the target description, activate hats mode — step 4a spawns 4 parallel hat agents (White/Black/Yellow/Green) instead of hive-mind workers. Mutually exclusive with--council; if both present,--hatswins. - If
$ARGUMENTScontains--deep: strip--deepfrom the target description, activate deep mode — runs the adversarial verification stage (step 4d) over the merged findings before synthesis. Combinable with any mode (standard /--council/--hats). - Auto-deep: even without
--deep, activate deep mode automatically when the target is high-stakes — an architectural or irreversible decision, cost-of-being-wrong rated expensive/catastrophic in step 2, or an M+ effort plan. When auto-triggering, tell the user one line: "High-stakes target — running deep verification." - If no arguments: conversation-context inference — scan recent conversation turns (both user and assistant) to identify the most significant unchalllenged decision, plan, or proposal. Priority order:
- A plan or architecture decision being actively discussed
- A proposal the user described or asked about
- Your own most recent substantive recommendation
- A trade-off or choice where alternatives weren't explored
- Extract: the decision/plan itself, the key constraints mentioned, and any assumptions stated or implied.
- Frame it naturally: "I see we're discussing [X]. Let me stress-test that." — not "Let me challenge my last answer."
- If the conversation has no substantive decision context (e.g., session just started, only greetings), then ask what to target.
- If
-
Scope discovery — before launching challengers, ask 2-4 targeted questions that could change the challenge outcome.
First, think (silently): given what's being challenged, what dimensions are non-obvious but consequential? What does Claude not know yet that would change which findings matter?
Then surface 2-4 questions via a single AskUserQuestion call. Choose from the dimensions below — pick the ones most relevant to the target. Skip generic process questions.
Dimension When to ask Example option set Deadline pressure Plan or implementation work "this week" / "this month" / "no fixed date" Cost of being wrong Architecture or migration "cheap (refactor)" / "expensive (data migration)" / "catastrophic (prod incident)" What's been tried Recurring problem or refactor "first attempt" / "one prior approach" / "multiple stalled attempts" Stakeholder breadth Anything visible externally "just me" / "one other person" / "wider team" / "external users" Constraints already locked Mid-project decisions "nothing locked yet" / specific commitments listed Hard ceiling on scope Sprawling proposals "S" / "M" / "L" / "explicitly unbounded" Gemini grounding Brana-domain decisions — user wants to skip "run agy (Recommended)" / "skip — no Brana docs apply"
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.
- 21d ago Changed · +8 lines ca0170986315
- 1mo ago First seen · 322 lines · 26 tokens per session scan A ce32194df256
challenge is a skill published in the GitHub repository martineserios/thebrana (3 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 6,086 once invoked, about $0.0001 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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