Borrowing it
Nothing to install: this file belongs to nijosmsft/etw-mcp. 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/nijosmsft/etw-mcp/master/CLAUDE.mdgit clone --depth 1 https://github.com/nijosmsft/etw-mcpWrote 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/instructions/nijosmsft/etw-mcp/claude-md)<a href="https://agentmods.dev/instructions/nijosmsft/etw-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/nijosmsft/etw-mcp/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/nijosmsft/etw-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/nijosmsft/etw-mcp/claude-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.04145 | $0.04145 |
| Opus 5.5 | $0.01658 | $0.01658 |
| Sonnet 5.5 | $0.00829 | $0.00829 |
| Haiku 4.5 | $0.00415 | $0.00415 |
Grade A, and why
etw-mcp CLAUDE.md 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 2mo 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
Guidance for Claude Code (and other AI assistants) when working on the etw-mcp source. For end-user docs (install, MCP config, tool list), see README.md.
What this repo is
An MCP server that wraps xperf.exe so AI assistants can analyze Windows WPR/ETW traces (.etl). Python 3.11+, packaged with uv, served over stdio via FastMCP. Windows-only — every analysis tool ultimately runs xperf as a subprocess.
Layout
src/etw_analyzer/
server.py ← entry point: imports each tools.* module to register @mcp.tool()s, then mcp.run("stdio")
app.py ← single FastMCP instance ("etw-trace-analyzer") + server instructions
trace_state.py ← TraceData dataclass + registry (make_trace_id, register/get/require_trace, list_loaded_trace_ids)
tools/ ← one module per tool group; each calls @mcp.tool() at import time
trace_mgmt.py ← list_traces, load_trace, list_loaded_traces, unload_trace, trace_info, check_symbols, resolve_symbols
symbol_diagnostics.py ← diagnose_symbol_load, clean_stale_symbol_files
cpu_sampling.py ← get_cpu_samples, get_hot_functions
per_cpu.py ← get_per_cpu_summary, get_cpu_timeline
stack_analysis.py ← get_hot_stacks, get_function_callers, walk_stack, count_stacks, butterfly_chain
dpc_isr.py ← get_dpc_summary, get_dpc_per_cpu
context_switch.py ← get_lock_contention
memory.py ← get_memory_pools
system_info.py ← get_sysconfig, get_process_info, get_diskio_summary, get_trace_stats
compare.py ← compare_traces
summary.py ← analyze, export_analysis
capture_profiles.py ← list_capture_profiles, get_capture_profile, get_capture_commands, get_capture_instructions
profiles/ ← bundled .wprp capture profiles (cpu, cpu_dpc_isr, network, network_minimal, network_packets, xdp_cpumap, quic, ebpf, general) + metadata.py table including the pktmon pseudo-scenario
parsing/
wpa_exporter.py ← xperf subprocess wrapper, all output parsers, export_all_profiles (parallel)
csv_loader.py ← BOM/comma-aware CSV → DataFrame normalization
aggregator.py ← parse_cpu_filter, apply_filters, group/sum, percentiles, time_bucket
formatting/
markdown.py ← format_table, format_pct — every tool returns a markdown string
tests/ ← pytest, synthetic data only — no xperf or .etl required
pyproject.toml ← hatchling build, deps: mcp, pandas, pyarrow; dev: pytest
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.
- 2mo ago First seen · 199 lines · 4,145 tokens per session scan A 6a9a17a82aff
etw-mcp CLAUDE.md is an instructions file published in the GitHub repository nijosmsft/etw-mcp (12 stars, last pushed 1mo ago), licensed MIT. It adds 4,145 tokens to every session, about $0.0166 per session on Opus 5.5. 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.
etw-mcp CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| etw-mcp CLAUDE.mdnijosmsft/etw-mcp | Instructions file | 12 | 1mo ago | MIT | A | 4,145 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| vscode model-prompts.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 2,022 | GitHub Copilot |