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 dungnotnull/retro-emulator-config-optimization-agent-skill --skill retro-emulator-config-optimization-agent-skillgit clone --depth 1 https://github.com/dungnotnull/retro-emulator-config-optimization-agent-skillWrote 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/dungnotnull/retro-emulator-config-optimization-agent-skill/retro-emulator-config-optimization-agent-skill)<a href="https://agentmods.dev/skills/dungnotnull/retro-emulator-config-optimization-agent-skill/retro-emulator-config-optimization-agent-skill"><img src="https://agentmods.dev/badge/skills/dungnotnull/retro-emulator-config-optimization-agent-skill/retro-emulator-config-optimization-agent-skill/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/dungnotnull/retro-emulator-config-optimization-agent-skill/retro-emulator-config-optimization-agent-skill"><img src="https://agentmods.dev/badge/skills/dungnotnull/retro-emulator-config-optimization-agent-skill/retro-emulator-config-optimization-agent-skill.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 | $0.00000 | $0.02955 |
| Opus 5 | $0.00000 | $0.01477 |
| Sonnet 5 | $0.00000 | $0.00591 |
| Haiku 4.5 | $0.00000 | $0.00296 |
Grade A, and why
retro-emulator-config-optimization-agent-skill 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 11d 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 — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL.md - Skill 200: retro-emulator-config-optimization
Comprehensive skill-registry documentation for the production-grade, modular, evidence-backed Retro Emulation Configuration & Display Latency harness. This file is the canonical reference for how skills are registered, resolved, executed, and validated, including the I/O JSON schemas, the tool registry, the hook lifecycle, the type-safe configuration, and the token/context-window management strategy.
1. What this skill does
retro-emulator-config-optimization turns Claude into a Senior Retro
Emulation Configuration & Display Latency Specialist. It gathers authoritative
real-time and reference data, applies recognized domain methods, integrates an
auto-updating academic knowledge base, and delivers risk/limitation-disclosed
outputs. The deterministic part of the analysis is delegated to an offline,
CI-testable tool (tools/emulator_config_analyzer.py); the LLM reserves
judgment for the context the tool cannot encode.
2. Architecture at a glance
USER INPUT
|
main.md (retro-emulator-config-optimization)
|-- Pre-Flight language detection (en/vi)
|-- router.md (chain-of-thought router) -- resolves ordered sub-skill plan
|
+-- sub-gather-requirements -> requirements object
+-- sub-evidence-collector -> evidence bundle (+ optional analyzer scorecard)
+-- sub-core-analysis -> optimized config + Best/Base/Worst scenarios
+-- sub-knowledge-updater -> 3-5 Tier-labeled citations + gap flags
+-- sub-advisor -> verdict + evidence chain + remediation
|
+-- Quality Gate Review (U1-U6 + G1-G4) -> deliver report
Cross-cutting: config/settings.py (Settings, flags, token budgets),
hooks/lifecycle.py (HookManager + structured events), tools/tool_registry.py
(typed tools with JSON schemas), references/ (grounding), scripts/
(automation), assets/ (diagrams + schemas). See assets/architecture.mmd.
3. Skill registry
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.
- 11d ago First seen · 294 lines · 0 tokens per session scan A bbdb45a92cea
retro-emulator-config-optimization-agent-skill is a skill published in the GitHub repository dungnotnull/retro-emulator-config-optimization-agent-skill (5 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,955 tokens. 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 2026-08-31.
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