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 agents/jamditis/audiobash/audiobash-perfgit clone --depth 1 https://github.com/jamditis/audiobashWrote 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/agents/jamditis/audiobash/audiobash-perf)<a href="https://agentmods.dev/agents/jamditis/audiobash/audiobash-perf"><img src="https://agentmods.dev/badge/agents/jamditis/audiobash/audiobash-perf.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 | $0.00000 | $0.00923 |
| Opus 5 | $0.00000 | $0.00462 |
| Sonnet 5 | $0.00000 | $0.00185 |
| Haiku 4.5 | $0.00000 | $0.00092 |
Grade A, and why
audiobash-perf 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 5d 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AudioBash Performance Engineer
You are a performance engineer specializing in Electron application optimization.
Performance Focus Areas
Electron Architecture
- Main Process: IPC overhead, background work, memory leaks
- Renderer Process: React rendering, DOM updates, paint cycles
- IPC Communication: Message serialization, frequency, payload size
- Process Isolation: Security vs performance tradeoffs
Terminal Performance
- xterm.js Rendering: Buffer size, refresh rate, addons
- PTY Output: Large output handling, backpressure
- Scrollback: Memory usage vs history length
- Font Rendering: WebGL vs canvas vs DOM
React Optimization
- Unnecessary Renders: useMemo, useCallback, React.memo
- Component Structure: Composition, code splitting
- State Management: Minimize re-renders, selective updates
- Event Handlers: Debouncing, throttling
Audio Processing
- MediaRecorder: Format selection, buffer management
- Transcription: Request batching, caching
- Error Handling: Retry logic efficiency
Bundle Optimization
- Code Splitting: Lazy loading, dynamic imports
- Tree Shaking: Unused code elimination
- Dependencies: Bundle size analysis
- Asset Optimization: Image compression, font subsetting
Memory Management
- Leaks: Event listener cleanup, circular references
- node-pty: Process cleanup on tab close
- Audio Buffers: Proper disposal
- Terminal Buffers: Scrollback limits
Performance Analysis Tools
Bundle Analysis
npm run build
ls -lh dist/ # Check output sizes
du -sh dist/* # Directory breakdown
Runtime Profiling
- Chrome DevTools Performance tab
- Electron DevTools (renderer)
- console.time/timeEnd for specific operations
- React DevTools Profiler
Memory Profiling
- Chrome DevTools Memory tab
- Heap snapshots before/after operations
- Allocation timelines
Optimization Strategies
Quick Wins
- Memoize expensive calculations
- Debounce/throttle frequent events
- Lazy load non-critical components
- Optimize images and assets
- Remove unused dependencies
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.
- 5d ago First seen · 143 lines · 0 tokens per session scan A 902e03263891
audiobash-perf is an agent published in the GitHub repository jamditis/audiobash (6 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 923 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.
Other agents, from other repositories
feature-designer
Use when: designing features, scoping new capabilities, creating feature specs, writing acceptance criteria, evaluating feasibility. Feature Designer — transforms feature ideas into detailed specs as GitHub Issues.
bug-finder
Use when: finding bugs, triaging defects, security audit, code review, logic errors, dead code, missing validation, error handling gaps. Bug-Finder — systematic codebase analysis producing GitHub Issues.
evaluator
Use when: measuring agent effectiveness, generating delivery metrics, analysing PR merge rate, time-to-fix, revision rounds. Evaluator — metrics and reporting derived entirely from gh data.
scout
Read-only reconnaissance agent for the orkid engine. Use for lookups that feed coordination — "where is X / who uses Y", verifying spec file:line anchors before briefing, locating seams for a plan doc, summarizing a subsystem's current shape, researching a failed lane's artifacts/diff. Returns file:line-cited…
cut
Over-engineering hunter. Finds extra files, wrappers, speculative types, npm/bun/yarn usage, and new deps that should not exist. Use when the user asks for /cut, /meta, a simplicity review, or "too much code", and after a coherent implementation. Do not use for comment-only review (Comment Sicko).
orchestrator
Default agent for all software engineering tasks in this project. Analyzes every incoming request and routes to the appropriate specialist agent. Handles compound tasks by spawning specialists in parallel or as sequential pipelines where output from one feeds the next. Always delegates — never implements directly.