mcpbeat Sign in

Proteomexchange Skill for Codex

Submit compact ProteomeXchange PROXI requests for datasets, libraries, peptidoforms, proteins, PSMs, spectra, and USI examples. Use when a user wants concise PROXI summaries

3k tokens
context cost
the whole folder, loaded on every use
3
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
4915
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/openai/plugins --skill proteomexchange-skill

What comes with it

10 834 bytes besides the instruction
agents/openai.yaml
scripts/rest_request.py

The instruction itself

6 sections, as written by the author

Operating rules

  • Use scripts/rest_request.py for all ProteomeXchange PROXI calls.
  • Use base_url=https://proteomecentral.proteomexchange.org/api/proxi/v0.1.
  • Collection endpoints are better with max_items=10; targeted identifier lookups usually do not need max_items.
  • Keep requests narrow by identifier, spectrum, or dataset whenever possible.
  • Re-run requests in long conversations instead of relying on older tool output.
  • Treat displayed ... in tool previews as UI truncation, not literal request content.

Execution behavior

  • Return concise markdown summaries from the script JSON by default.
  • Prefer these paths: datasets, datasets/<identifier>, libraries, peptidoforms, proteins, psms, spectra, and usi_examples.
  • If the user needs the full payload, set save_raw=true and report the saved file path.

Input

  • Read one JSON object from stdin.
  • Required fields: base_url, path
  • Optional fields: method, params, headers, json_body, form_body, record_path, response_format, max_items, max_depth, timeout_sec, save_raw, raw_output_path
  • Common PROXI patterns:
  • {"base_url":"https://proteomecentral.proteomexchange.org/api/proxi/v0.1","path":"datasets","max_items":10}
  • {"base_url":"https://proteomecentral.proteomexchange.org/api/proxi/v0.1","path":"datasets/PXD000001"}
  • {"base_url":"https://proteomecentral.proteomexchange.org/api/proxi/v0.1","path":"usi_examples","max_items":10}

Output

  • Success returns ok, source, path, method, status_code, warnings, and either compact records or a compact summary.
  • Use raw_output_path when save_raw=true.
  • Failure returns ok=false with error.code and error.message.

Execution

echo '{"base_url":"https://proteomecentral.proteomexchange.org/api/proxi/v0.1","path":"datasets","max_items":10}' | python scripts/rest_request.py

References

  • No additional runtime references are required; keep the import package limited to this file and scripts/rest_request.py.

Other skills for the same job

different authors, same section of the catalogue
Skill Creator
by anthropics
vendor ×10

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

56k tokens scripts
Geo Database
by christophacham
×4

Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.

12k tokens
Pymc Bayesian Modeling
by christophacham
×4

Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.

24k tokens scripts
Pymoo
by christophacham
×4

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

19k tokens scripts
Statsmodels
by ComeOnOliver
×4

Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.

41k tokens
Add Uint Support
by pytorch
vendor ×3

Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.

2k tokens
At Dispatch V2
by pytorch
vendor ×3

Convert PyTorch AT_DISPATCH macros to AT_DISPATCH_V2 format in ATen C++ code. Use when porting AT_DISPATCH_ALL_TYPES_AND*, AT_DISPATCH_FLOATING_TYPES*, or other dispatch macros to the new v2 API. For ATen kernel files, CUDA kernels, and native operator implementations.

2k tokens
Docstring
by pytorch
vendor ×3

Write docstrings for PyTorch functions and methods following PyTorch conventions. Use when writing or updating docstrings in PyTorch code.

3k tokens

How to use it

Copy the folder

Take openai/proteomexchange-skill from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.