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 instructions/torchedhat/torchtalk/claude-mdgit clone --depth 1 https://github.com/TorchedHat/torchtalkWrote 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/torchedhat/torchtalk/claude-md)<a href="https://agentmods.dev/instructions/torchedhat/torchtalk/claude-md"><img src="https://agentmods.dev/badge/instructions/torchedhat/torchtalk/claude-md.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 | $0.01205 | $0.01205 |
| Opus 5 | $0.00602 | $0.00602 |
| Sonnet 5 | $0.00241 | $0.00241 |
| Haiku 4.5 | $0.00120 | $0.00120 |
Grade A, and why
torchtalk 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 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code when working with code in this repository.
Commands
# Install
pip install -e .
pip install -e ".[dev]"
# Test
pytest
PYTORCH_SOURCE=/path/to/pytorch pytest tests/test_binding_detector_pytorch.py
# Lint
ruff check src/torchtalk/
ruff format src/torchtalk/
# Run MCP server
python -m torchtalk mcp-serve --pytorch-source /path/to/pytorch
Project Structure
src/torchtalk/
├── server.py # MCP server (7 tools: status + 6 query)
├── cli.py # CLI (torchtalk mcp-serve)
├── formatting.py # Response formatting (CompactText/Markdown)
└── analysis/
├── binding_detector.py # pybind11/TORCH_LIBRARY detection (tree-sitter)
├── cpp_call_graph.py # C++ call graph extraction (libclang)
├── python_analyzer.py # Python module/class analysis (AST)
├── patterns.py # Search directories, exclusion patterns
└── helpers.py # Utility functions
Architecture
MCP server providing cross-language binding analysis for PyTorch.
Server (server.py): FastMCP-based, auto-builds and caches index from PyTorch source. Background thread for C++ call graph.
Analysis (analysis/): BindingDetector (tree-sitter), CppCallGraphExtractor (libclang, 60K+ functions), PythonAnalyzer (AST).
Data Sources: native_functions.yaml, derivatives.yaml, compile_commands.json, tree-sitter AST.
Cache: ~/.cache/torchtalk/ — bindings (~10MB), call graph (~50MB).
MCP Tools
IMPORTANT: Use mcp__torchtalk__* tools directly. Do NOT import or run Python code from torchtalk.server.
| Tool | Description |
|---|---|
get_status() |
TorchTalk readiness summary across bindings, call graph, modules, tests |
trace(func, focus?) |
Trace any PyTorch op: Python → YAML → C++ → file:line |
search(query, mode?, backend?) |
mode="bindings": dispatch registrations. mode="kernels": CUDA kernel launches |
graph(func, mode?, depth?, fuzzy_all_levels?, walk_python?, focus?) |
mode="callers": inbound. mode="calls": outbound. mode="impact": transitive callers (depth/fuzzy_all_levels/walk_python/focus apply to impact only) |
modules(name, mode?, focus?) |
mode="trace": class details (focus="full" adds bases/docstring). mode="list": browse by category ("nn", "optim", "all") |
tests(query?, mode?, limit?, focus?) |
mode="find": search tests (focus narrows to functions/classes/files). mode="utils": list utilities (query/focus ignored). mode="file_info": test file details |
affected(funcs, depth?) |
Map changed C++ functions (comma-separated) to impacted Python test files |
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 · 110 lines · 1,205 tokens per session scan A 10f357d69c3a
torchtalk CLAUDE.md is an instructions file published in the GitHub repository TorchedHat/torchtalk (11 stars, last pushed 7d ago), licensed MIT. It adds 1,205 tokens to every session, about $0.0060 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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AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
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AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.