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/dylanroscover/embody/claude-mdgit clone --depth 1 https://github.com/dylanroscover/EmbodyWrote 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/dylanroscover/embody/claude-md)<a href="https://agentmods.dev/instructions/dylanroscover/embody/claude-md"><img src="https://agentmods.dev/badge/instructions/dylanroscover/embody/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 5.1 | $0.02721 | $0.02721 |
| Opus 5 | $0.01360 | $0.01360 |
| Sonnet 5 | $0.00544 | $0.00544 |
| Haiku 4.5 | $0.00272 | $0.00272 |
Grade A, and why
Embody 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 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Embody + Envoy
Project Overview
Embody is a TouchDesigner extension that automates externalization of COMP and DAT operators to version-control-friendly files (.tox, .py, .json, .xml, etc.). It solves the problem of TouchDesigner's binary .toe files being impossible to diff/merge in git.
Envoy is an MCP (Model Context Protocol) server embedded inside Embody that lets Claude Code create, modify, connect, and query TouchDesigner operators programmatically -- plus manage Embody externalizations.
Critical Rules
- Prefer the externalized network file for reading TDXN-externalized COMPs -- these are YAML on disk with complete network structure (operators, parameters, connections, positions, flags, DAT content, annotations). Reading them directly is faster than MCP round-trips. Never glob for an extension: Embody writes
.tdxnas of v6.1.0 and keeps writing.tdnfor any COMP externalized earlier, so a project legitimately holds a mix. Checkexternalizations.tsv(strategy column) or callget_externalizationsto identify them -- the strategy value is stilltdn, unchanged by the rename; searching fortdxnthere finds nothing. To edit: modify the.tdnfile on disk, then always callimport_networkvia MCP with the COMP path, the parsed network, andclear_first=Trueto reload it in TD. Never leave a.tdnedit unreloaded -- the user must see updates immediately in TD. Use MCP when you need live runtime state (evaluated expressions, cook errors) or for non-TDN operators. For project-wide questions -- who references this operator, what is the signal-flow topology, where is X used -- read the project-wide.tdnsnapshot with Grep/Read before making MCP calls; the Externalize Full Project pulse (ext.Embody.externalizeProject()) writes one (see the Embody parameters, or the setup wizard's externalize step). One grep over that file answers what would otherwise cost many round-trips. - Use Envoy MCP tools for live TD state and non-TDN operators -- NEVER say "I can't edit that because it's in a .tox" or "these are binary files I can't access." For operators not externalized as TDN, use MCP tools to inspect and modify them. The filesystem holds externalized files (
.py,.tox,.tdn,.json,.xml, etc.); MCP is for interacting with live operator state inside TD. - NEVER create operators under
/local--/localis volatile storage, not saved with the.toefile. Place new COMPs in the container that holds theEmbodyCOMP (op.Embody.parent().path, the level the user chose) -- or a network the user has deliberately opened -- never/localand never the bare root/. See/create-operatorstep 1. - Do NOT assume network paths -- never guess
/project1. Usequery_networkon/to discover the actual root structure. - Default new COMPs to Embody's container --
execute_pythonwithresult = op.Embody.parent().pathreturns the same home every run (the consistency anchor). Build inui.panes.current.owner.pathonly when the user has deliberately navigated into a content network, and never treat bare/as that home. See/create-operatorstep 1. - Always consult the TD wiki before writing TD Python code OR claiming TD behavior -- confirm API behavior, file formats, and application features against official Derivative documentation even if you're confident. Never assume a TD feature, file type, or convention exists without a verified source.
- Binary files (
.toe,.tox) -- use MCP tools to inspect contents, not the filesystem. - Always check for errors after creating operators --
get_op_errorswithrecurse=trueimmediately after creating and connecting operators. - Favor annotations over OP comments -- use
create_annotationfor documenting operators and groups. - Always analyze log files after MCP operations -- read
dev/logs/for the complete picture. Ring buffer only holds 200 entries. - Always update unit tests when modifying project code -- check whether existing tests assert against changed behavior.
- Batch repetitive MCP operations -- never make 3+ individual calls to the same tool. Use
batch_operationsto combineset_op_position,connect_ops,set_parameter,set_op_flags, etc. into a single request. For complex logic (conditionals, loops, computed values), useexecute_pythoninstead. Each MCP round-trip costs tokens and latency -- minimize them. - Prefer the operator-creating MCP tools (
create_op,copy_op,create_extension) over rawexecute_python-- they auto-position, lint layout, and (when the EnvoyAutoexternalizepreference isDATs/COMPs/both) auto-externalize new COMPs (TDN) and DATs (source) at their boundary -- additively, never inside an already-externalized ancestor. Acopy_opgets a fresh externalization at its own path (inherited source tags/file-refs are cleared, so the copy never shares or overwrites the source's files);create_extensionexternalizes the host COMP it creates (its code DAT is captured inside). Batch viabatch_operations. Reach forexecute_python/comp.create()/.copy()only when you genuinely need computed/looped creation or connection-preservingcopyOPs; those bypass auto-externalization (Envoy rides anAUTO-EXTERNALIZE BYPASSwarning back on the response) and require manual layout + tagging.
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 Changed afef44bc91a5
- 6d ago First seen · 101 lines · 2,721 tokens per session scan A fd5628c137de
Embody CLAUDE.md is an instructions file published in the GitHub repository dylanroscover/Embody (169 stars, last pushed 2d ago), licensed MIT. It adds 2,721 tokens to every session, about $0.0136 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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