Borrowing it
Nothing to install: this file belongs to namastexlabs/automagik-cli. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/namastexlabs/automagik-cli/main/.claude/commands/speed.mdgit clone --depth 1 https://github.com/namastexlabs/automagik-cliWrote 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/commands/namastexlabs/automagik-cli/speed)<a href="https://agentmods.dev/commands/namastexlabs/automagik-cli/speed"><img src="https://agentmods.dev/badge/commands/namastexlabs/automagik-cli/speed.svg" alt="Measured on agentmods" 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 | $0.03640 |
| Opus 5 | $0.00000 | $0.01820 |
| Sonnet 5 | $0.00000 | $0.00728 |
| Haiku 4.5 | $0.00000 | $0.00364 |
Grade A, and why
speed 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 3d 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 — 509 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/speed
allowed-tools: Task(), Read(), Write(), Edit(), MultiEdit(), Glob(), Grep(), Bash(), LS(), TodoWrite(), WebSearch(), mcp__zen__, mcp__search-repo-docs__, mcp__ask-repo-agent__, mcp__genie_memory__, mcp__send_whatsapp_message__, mcp__wait__* description: Genie Speed Optimization Framework - AI-assisted performance optimization with generate-and-verify approach
Genie Speed Optimization Framework
Overview
The Genie Speed Optimization Framework is an AI-assisted performance optimization system inspired by Codeflash that follows a "generate and verify" approach. It uses multi-model consensus to generate optimizations, rigorously verifies performance improvements, and maintains code correctness through comprehensive testing.
Core Philosophy
- Generate and Verify: AI models propose optimizations, empirical benchmarking validates improvements
- One Commit Per Optimization: Each optimization attempt gets its own commit for traceability
- Automatic Revert: Failed optimizations are automatically reverted to prevent regressions
- Multi-Model Consensus: Complex optimizations require agreement from multiple AI models
- Minimum Runtime Principle: Performance measured using best-of-N runs to minimize noise
Framework Components
1. Benchmarking Infrastructure (scripts/speed/)
- benchmark_runner.py: Core benchmarking engine with minimum runtime measurement
- performance_profiler.py: Code profiling and bottleneck identification
- noise_reduction.py: Statistical techniques for stable performance measurement
- baseline_manager.py: Manages performance baselines and regression detection
2. Git Automation (scripts/speed/git/)
- checkpoint_manager.sh: Creates optimization checkpoints and manages branches
- auto_revert.sh: Automatically reverts failed optimizations
- commit_automation.py: Handles structured commits with performance metadata
- conflict_resolver.py: Manages git conflicts during optimization workflows
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.
- 3d ago First seen · 509 lines · 0 tokens per session scan A 00c1646a0b02
speed is a command published in the GitHub repository namastexlabs/automagik-cli (6 stars, last pushed 9mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,640 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 2026-09-04.
Other commands, from other repositories
bugfix
Bug fix workflow: root cause analysis → user review → regression test + fix via TDD.
verify-bug
Post-merge UAT verification workflow. Walks JIRA reproduce steps, performs comparative audits (Before/After), attaches evidence to JIRA, and transitions status on PASS.
timeout-fix
A procedure for diagnosing and fixing tests that exceed their time limit by finding causes such as slow processing, hanging network calls, deadlocks, heavy setup, or leaked resources.
ui-aqa-flow-test-report-analysis
Phase 7 Test Report Analysis of ui-aqa-flow.
api-aqa-flow-execution-and-report-analysis
Phase 6 Execution & Report Analysis of api-aqa-flow (USER INTERACTION REQUIRED).
qa-changes
This skill should be used when the user asks to "QA a pull request", "test PR changes", "verify a PR works", "functionally test changes", or when an automated workflow triggers QA validation of code changes. Provides a structured methodology for setting up the environment, exercising changed behavior, and reporting…