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 skills/teklabsdigital/x2-method/implementnpx skills add teklabsdigital/x2-method --skill implementgit clone --depth 1 https://github.com/teklabsdigital/x2-methodWhat 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 | $0.00071 | $0.01154 |
| Opus 5 | $0.00036 | $0.00577 |
| Sonnet 5 | $0.00014 | $0.00231 |
| Haiku 4.5 | $0.00007 | $0.00115 |
Grade A, and why
implement 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 2d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 2d ago First seen · 84 lines · 71 tokens per session scan A 582c19902d82
implement is a skill published in the GitHub repository teklabsdigital/x2-method (15 stars, last pushed 26d ago), with no licence file. It adds 71 tokens to every session and 1,154 once invoked, about $0.0004 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.
Other skills, from other repositories
autoimplement
Auto-advance a multi-phase plan: dispatch a subagent per phase, chain /review /pitfall-verification at each boundary, stop on actionable findings. Use for "autoimplement", "run this plan end-to-end", "auto-advance phases".
swiftui-design-consultation
Apple-canon design system for SwiftUI projects: produces DESIGN.md + a Swift Package starter (semantic colors, SF Pro, Liquid Glass, motion, accessibility). Use when starting or refreshing a SwiftUI design system.
ios-native-review
After a PRD/spec/plan for an iOS app, before implementation: validate the artifact against Apple HIG (iOS) via WebFetch citations. Asks "is this iOS-native?" — complements pitfall-verification and quality-review.
office-hours-track-aware
Track-aware wrapper for gstack /office-hours: runs the session, detects native vs web, renders + opens DESIGN.html before the approval gate. Use when starting a new product idea or brainstorming.
verify-and-land
Build the checked-out branch, launch that exact app, let the user confirm the fix is really there, then push and offer merge or PR.
e2e-route
Pure dispatcher: picks the right E2E executor for a Swift test request from context (platform × intent × verification kind) and hands off. Routes to the scaffold/MCP-sim/QA/design-review skills.