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 xdg/xdg-claude --skill adversarial-implementationgit clone --depth 1 https://github.com/xdg/xdg-claudeWrote 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/xdg/xdg-claude/adversarial-implementation)<a href="https://agentmods.dev/skills/xdg/xdg-claude/adversarial-implementation"><img src="https://agentmods.dev/badge/skills/xdg/xdg-claude/adversarial-implementation.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00052 | $0.01682 |
| Opus 5 | $0.00026 | $0.00841 |
| Sonnet 5 | $0.00010 | $0.00336 |
| Haiku 4.5 | $0.00005 | $0.00168 |
Grade A, and why
adversarial-implementation 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 8d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task: $ARGUMENTS
(If no task is provided, read TODO.md, if it exists. Implement the next incomplete
subsection. If there is no TODO.md file, prompt the user for instructions.)
Adversarial Implementation Protocol
When implementing from TODO.md:
- Implementation unit: Individual checkboxes (keeps subagent sessions manageable)
- Completion unit (aka "subsection"): The immediate parent heading of a group of checkboxes—i.e., the most specific heading that directly contains them, not any ancestor.
Example TODO structure:
### 3.1 OAuth Setup
#### 3.1.1 Configure provider
- [ ] Add client ID
- [ ] Add client secret
#### 3.1.2 Implement callback
- [ ] Handle redirect
Here, 3.1.1 and 3.1.2 are completion units (each is a subsection directly containing checkboxes).
3.1 OAuth Setup is NOT a completion unit—it's a parent grouping.
A completion unit is complete only when ALL its checkboxes are checked—including any that require human verification.
Isolated subagents
Whenever this guide says to invoke an isolated subagent, fall back to a general agent if the isolated subagent doesn't exist. In either case, use model 'opus' and effort 'low' for subagents unless otherwise instructed by the user.
Phase 1: Plan the Subsection
For the next incomplete Phase subsection:
- Read ALL checkboxes within the subsection
- Categorize each checkbox:
- Automatable: Code changes, automated tests
- Human-required: Browser interactions, visual verification, manual testing
- Process automatable items one at a time (or in small logical batches) through Phases 2-4 before moving to the next item
- Track which items are complete within the subsection
- If subsection has NO automatable items, skip directly to Phase 6
Phase 2: Implement Single Item via Subagent
For each automatable checkbox:
- Spawn an isolated task subagent (if one exists, or a general subagent otherwise) with this prompt structure:
Task: [specific checkbox item]
Context files: TODO.md, any other relevant specs or instructions (OMIT code
files; the subagent can find these on its own)
Constraints: [project rules, style guide refs]
Acceptance criteria: [the specific checkbox, explicitly stated]
Output: Implement and report a concise summary of what you changed.
- Do NOT provide the full codebase—give minimal necessary context so you minimize use of the main context. Include: TODO.md, relevant specs, file paths to modify. Exclude: file contents the subagent can read itself, unrelated modules.
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.
- 8d ago First seen · 174 lines · 52 tokens per session scan A 15f034e06cc6
adversarial-implementation is a skill published in the GitHub repository xdg/xdg-claude (20 stars, last pushed today), licensed Apache-2.0. It adds 52 tokens to every session and 1,682 once invoked, about $0.0003 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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