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 neverinfamous/memory-journal-mcp --skill adversarial-plannergit clone --depth 1 https://github.com/neverinfamous/memory-journal-mcpWrote 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/neverinfamous/memory-journal-mcp/adversarial-planner)<a href="https://agentmods.dev/skills/neverinfamous/memory-journal-mcp/adversarial-planner"><img src="https://agentmods.dev/badge/skills/neverinfamous/memory-journal-mcp/adversarial-planner/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/neverinfamous/memory-journal-mcp/adversarial-planner"><img src="https://agentmods.dev/badge/skills/neverinfamous/memory-journal-mcp/adversarial-planner.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 | $0.00107 | $0.00972 |
| Opus 5 | $0.00053 | $0.00486 |
| Sonnet 5 | $0.00021 | $0.00194 |
| Haiku 4.5 | $0.00011 | $0.00097 |
Grade A, and why
adversarial-planner 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial Planner
A multi-pass planning and review system that produces high-quality plans by introducing structured adversarial critique stages. Plans pass through an iterative pipeline of drafting, review, refinement, and optional external validation — producing output optimized for correctness, performance, security, and maintainability.
When to Load
Load this skill when any of these apply:
- Creating an implementation plan for a new feature or architectural change
- Designing multi-file refactors or system migrations
- Planning project roadmaps, milestones, or sprint scopes
- The user asks for an adversarial or multi-pass review of a plan
- The user says "plan this", "review my plan", "critique this plan", "multi-pass plan", "architect this", "design this system", or "how should I build"
- You want to reduce confirmation bias in your own planning output
Adversarial Protocol
This skill follows the standard dual-agent adversarial pattern (Agent A: The Planner, Agent B: The Adversarial Reviewer). For the core pipeline rules, phase definitions, and agent switching protocols, read: ../adversarial-security/references/adversarial-base-protocol.md
For the planner-specific protocol with review dimensions, scoring weights, and output templates, read: references/multi-pass-protocol.md
External Validation (Phase 4)
Phase 4 triggers an independent validation pass using the GitHub CLI (gh copilot).
The copilot subcommand is built into modern gh CLI — no separate extension is
needed. This provides a fundamentally different model's perspective on the plan,
reducing confirmation bias that persists even after adversarial self-review.
For Copilot-specific prompt templates and integration details, read references/copilot-integration.md.
Prerequisites: gh CLI v2.x+ with gh auth status passing. If gh copilot
is not available, skip Phase 4 gracefully and note the skip in the journal entry.
What ships with it
4 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 · 90 lines · 107 tokens per session scan A 6a87a08a046f
adversarial-planner is a skill published in the GitHub repository neverinfamous/memory-journal-mcp (20 stars, last pushed 1mo ago), licensed MIT. It adds 107 tokens to every session and 972 once invoked, about $0.0005 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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