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/techymt/claude-code-superpowers/hot-pathsnpx skills add TechyMT/claude-code-superpowers --skill hot-pathsgit clone --depth 1 https://github.com/TechyMT/claude-code-superpowersWhat 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 | $0.00089 | $0.01692 |
| Opus 5 | $0.00044 | $0.00846 |
| Sonnet 5 | $0.00018 | $0.00338 |
| Haiku 4.5 | $0.00009 | $0.00169 |
Grade A, and why
hot-paths 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.
How it starts
The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hot Paths
The pattern
Claude Code has three hot paths: startup (module loading before first prompt), per-turn (context assembly before each API call), and per-tool-call (schema validation and permission checking for every tool use). Each has different performance constraints and different techniques.
For startup: use lazySchema() to defer Zod parsing, use feature() flags to eliminate dead code at build time, parallelize independent I/O with Promise.all(), and track timing with profileCheckpoint().
For per-turn: memoize expensive computations (git status, file system state) that don't change mid-conversation. Clear memoized values only when the underlying state actually changes.
For per-tool-call: lazySchema() ensures schema objects are built at most once per process lifetime (on first access), not once per call.
Why this matters
Claude Code starts a new process on every invocation. Users expect the prompt to appear in under a second. With ~512K lines of TypeScript across 1,884 files, naive module loading would be too slow. The techniques below are how the team keeps startup under a second on typical developer machines.
The per-turn hot path is also user-visible: every time the LLM needs to generate a response, Claude Code assembles a system prompt that includes git status, open file list, working directory, and recent file changes. This assembly runs before each API call. If it were slow, every turn would feel sluggish.
How to apply it
Startup:
- Wrap Zod schemas in
lazySchema(() => z.object({...}))fromutils/lazySchema.ts. The schema is built only when first accessed, not when the module loads. - Use
feature('FLAG_NAME')frombun:bundlefor conditional imports. Bun evaluates these at build time and tree-shakes unused code. An unused feature flag means the code is not included in the bundle. - Use
profileCheckpoint('label')to measure time between initialization steps during development. - For independent async initialization (config reads, keychain prefetch, MCP connection), use
Promise.all().
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 · 160 lines · 89 tokens per session scan A 7d4d55d94896
hot-paths is a skill published in the GitHub repository TechyMT/claude-code-superpowers (5 stars, last pushed 5mo ago), licensed MIT. It adds 89 tokens to every session and 1,692 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 2026-08-31.
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