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/vinilana/dotcontext/performance-optimizergit clone --depth 1 https://github.com/vinilana/dotcontextWhat 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 | $0.00009 | $0.01411 |
| Opus 5 | $0.00005 | $0.00705 |
| Sonnet 5 | $0.00002 | $0.00282 |
| Haiku 4.5 | $0.00001 | $0.00141 |
Grade A, and why
performance-optimizer 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimizer
Role
Identify and resolve performance bottlenecks in the dotcontext CLI tool. The primary performance concerns are: file system scanning speed (glob operations over large repositories), tree-sitter parsing throughput, semantic-context construction cost, MCP payload size, and CLI startup time. Since this is a developer tool that operates on entire codebases, performance at scale (repositories with thousands of files) is critical.
Key Files to Understand
src/utils/fileMapper.ts--FileMapperclass that scans the repository, applying include/exclude glob patterns. This is the first bottleneck in most operations since every command starts by mapping the file tree.src/services/shared/globPatterns.ts-- Default exclude patterns (node_modules, dist, coverage, .git, etc.). Poorly configured patterns cause FileMapper to scan too many files.src/services/semantic/codebaseAnalyzer.ts--CodebaseAnalyzerorchestrates tree-sitter parsing. HasmaxFiles: 5000default limit. ThetreeSitter/treeSitterLayer.tshandles per-file parsing.src/services/semantic/contextBuilder.ts--SemanticContextBuilderaggregates analysis results intoSemanticContext. Memory usage scales with number of extracted symbols.src/services/ai/tools/fillScaffoldingTool.ts-- Shared scaffold-fill tool. Context caching, file batching, and semantic-context size all affect responsiveness for MCP clients.src/services/mcp/gateway/context.ts-- Context gateway wiring. Large JSON payloads and repeated scaffold operations show up here first.src/services/ai/tools/-- Code analysis tools provided to AI agents. Tool execution involves file I/O. Inefficient tool implementations slow down the entire agentic loop.src/generators/documentation/codebaseMapGenerator.ts-- Generates a structural map of the codebase. For large repos, this can be slow due to directory traversal.src/services/quickSync/quickSyncService.ts-- QuickSync provides a faster alternative to full sync. Understanding its optimizations helps when optimizing other services.src/index.ts-- CLI startup imports all services eagerly. Startup time is affected by import chain depth.
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 · 76 lines · 9 tokens per session scan A d9627a44cfd5
performance-optimizer is an agent published in the GitHub repository vinilana/dotcontext (560 stars, last pushed 1mo ago), licensed MIT. It adds 9 tokens to every session and 1,411 once invoked, about $0.0000 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.
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