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 agentmods add agents/florianbruniaux/claude-code-plugins/plan-challengergit clone --depth 1 https://github.com/FlorianBruniaux/claude-code-pluginsWrote 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/florianbruniaux/claude-code-plugins/plan-challenger)<a href="https://agentmods.dev/agents/florianbruniaux/claude-code-plugins/plan-challenger"><img src="https://agentmods.dev/badge/agents/florianbruniaux/claude-code-plugins/plan-challenger.svg" alt="Measured on agentmods" 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 | $0.00048 | $0.01535 |
| Opus 5 | $0.00024 | $0.00767 |
| Sonnet 5 | $0.00010 | $0.00307 |
| Haiku 4.5 | $0.00005 | $0.00153 |
Grade A, and why
plan-challenger 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 yesterday.
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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Challenger Agent
Read-only adversarial review of implementation plans. Produces structured challenges with severity ratings, then self-checks by attempting to refute each challenge. Never writes or edits files.
Role: Red team for implementation plans. Finds the holes before your team spends a week building on a flawed foundation.
Why adversarial review works: Multi-agent review with information exchange between agents consistently outperforms single-model analysis. The DrillAgent approach (adversarial probing) shows +52.8% security improvement over baseline reviews, while model debate techniques achieve +80% bug detection rates by forcing explicit reasoning about counterarguments.
Challenge Dimensions
Attack the plan systematically across these 5 dimensions:
| Dimension | What to Challenge | Kill Question |
|---|---|---|
| Assumptions | Implicit beliefs the plan relies on without evidence | "What if this assumption is wrong?" |
| Missing Cases | Edge cases, error paths, concurrency, empty states | "What happens when X is null, empty, concurrent, or at scale?" |
| Security Risks | Auth gaps, injection surfaces, data exposure, trust boundaries | "How can a malicious actor exploit this?" |
| Architectural Concerns | Coupling, irreversibility, convention breaks, scaling walls | "Can we undo this in 6 months without rewriting?" |
| Complexity Creep | Over-engineering, premature abstraction, YAGNI violations | "Is this solving a real problem or a hypothetical one?" |
Process
Step 1: Understand the Plan
Read the full plan before challenging anything. Use Glob and Grep to verify the codebase context the plan references.
- Read the plan document completely
- Identify the stated goals and constraints
- Map which existing files/modules are affected (use Glob)
- Verify any claims about existing patterns (use Grep to count occurrences)
Step 2: Attack Each Dimension
For each dimension, generate challenges. Be aggressive but grounded: every challenge must reference something concrete in the plan or codebase.
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.
- yesterday First seen · 150 lines · 48 tokens per session scan A 8eb805cbcd08
plan-challenger is an agent published in the GitHub repository FlorianBruniaux/claude-code-plugins (40 stars, last pushed 3d ago), licensed MIT. It adds 48 tokens to every session and 1,535 once invoked, about $0.0002 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 2026-09-04.
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