Borrowing it
Nothing to install: this file belongs to Zuehlke/teststand-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/Zuehlke/teststand-mcp/main/CLAUDE.mdgit clone --depth 1 https://github.com/Zuehlke/teststand-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/zuehlke/teststand-mcp/claude-md)<a href="https://agentmods.dev/instructions/zuehlke/teststand-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/zuehlke/teststand-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/zuehlke/teststand-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/zuehlke/teststand-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 | $0.22925 | $0.22925 |
| Opus 5 | $0.11463 | $0.11463 |
| Sonnet 5 | $0.04585 | $0.04585 |
| Haiku 4.5 | $0.02293 | $0.02293 |
Grade A, and why
teststand-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 8d 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 — 1,143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TestStandMCP — Behavior Rules for Claude
Rebuilding a .seq 1:1 — export_sequence_file + import_sequence_file FIRST
For a whole-file reproduction, migration or bulk edit, use the export/import pair. It is the default path; the granular tools are for surgical single edits.
export_sequence_file(file_path) → writes <file>.model.json, returns a summary
create_sequence_file(dest, overwrite=true) → overwrite handles the close+delete dance
import_sequence_file(model_path, dest_file_path) → rebuilds everything, returns counts + warnings[]
diff_sequence_files(orig, dest) → verify the CONTENT (rows capped at 150 by default)
audit_type_consistency(dest, reference_file_path=orig) → verify the TYPE REGISTRY (the diff can't)
The import removes the destination's leftover MainSequence itself when the model has none, so there
is no delete_sequence step any more.
Measured 2026-07-29 on 8 sequences of TFW_MDC_com_Python.seq (47 steps, 13 object-oriented Python
steps, 5 LabVIEW .lvlibp steps, 1 cross-file SequenceCall): 3 MCP calls and ZERO FileDiffer
differences inside the imported scope (the only rows left are the 22 sequences not imported). The same
rebuild with the granular tools took ~700 calls, 3 diff iterations and left 224 differences.
The on-disk FORMAT is reproduced too — and the diff is blind to it (2026-07-31)
A .seq is stored either as compressed binary (TOF1 magic, zlib body — step names are NOT
text-searchable) or as XML (a UTF-8 BOM then <?xml), and the engine's default for a new file is
binary. MEDELA_TFW's real files are XML, so a rebuild used to come out binary: content-identical
(diff_sequence_files says identical) yet different in every byte, 25 KB against 3.4 MB on
TFW_MDC_com_Python — ×133, pure serialization.
- The export now captures the source format (
file.fileFormatin the model) and the import reproduces it by default — nothing to pass for a 1:1 rebuild; the outcome reportsfileFormat. get_file_propertiesreportsfileFormat;create_sequence_file,save_sequence_file,set_file_propertiesandimport_sequence_filetakefile_format=binary|xml|ini. The format is stored IN the file, so it survives; an ordinary save never converts it back.- Before reading a large size drop as data loss, check the first bytes (
TOF1vs<?xml). - XML is the format to pick for anything that lives in git — binary
.seqdiffs are opaque. - This is the serialization, NOT the TestStand version target (that is the
versionfield).
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.
- 8d ago First seen · 1,143 lines · 22,925 tokens per session scan A 66ac67bb974d
teststand-mcp CLAUDE.md is an instructions file published in the GitHub repository Zuehlke/teststand-mcp (24 stars, last pushed 24d ago), licensed MIT. It adds 22,925 tokens to every session, about $0.1146 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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