matchms SKILL.md skillA
matchms from k-dense-ai/scientific-agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add k-dense-ai/scientific-agent-skills/matchms@v2.3Pins v2.3 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- k-dense-ai/scientific-agent-skills
- Path
skills/matchms/SKILL.md- Versions recorded
- 6
- Latest version
- v2.3, committed Oct 1, 2026
- First version recorded
- May 27, 2026
- Size
- 12,821 bytes
- Repository stars
- 56,497
- License
- MIT
Processes, cleans, compares, and searches tandem mass spectra with matchms. Use for MS/MS file I/O, metadata harmonization, peak filtering, spectral similarity, library matching, score matrices, and molecular-similarity networks. Use pyopenms instead for LC-MS feature detection or proteomics pipelines.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Matchms ## Purpose and Scope Matchms is a Python package for importing, cleaning, processing, and comparing tandem mass spectra. This skill targets **matchms 0.33.1**, released 2026-06-08, verified again on 2026-10-01. Older tutorials can use removed names; see the migration reference. Use matchms for: - MS/MS library search and query-versus-reference scoring - Metadata harmonization, adduct/precursor handling, and peak filtering - Cosine, modified-cosine, neutral-loss, approximate, and entropy scoring - Structured score matrices, top-hit extraction, and spectral networks - MGF, MSP, mzML, mzXML, JSON, mzSpecLib, and metabolomics-USI workflows Do not use matchms as a replacement for: - LC-MS feature detection, chromatographic alignment, peptide identification, or protein quantification — use pyopenms - Vendor raw-file conversion — convert to mzML/mzXML first - A validated compound-identification protocol — similarity is evidence, not proof of identity ## Install the Verified Release Create or activate an environment, then install the release used by this skill: ```bash uv pip install "matchms==0.33.1" ``` Verify the runtime: ```bash …
Read the whole file at its exact version.
How to install
mdr add k-dense-ai/scientific-agent-skills/matchms@sha256:1bde0e20f69f99dfThe line at the top of this page pins the label v2.3, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_4gskwbtxp2n6rpow)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 6 versions of this file, between May 27, 2026 and Oct 1, 2026, about one every 25 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v2.3 latest | 2026-10-01 | a92663a | 12,821 B | A | view · diff |
| v2.2 | 2026-09-30 | ce9e6e9 | 11,835 B | A | view · diff |
| v2.1 | 2026-09-02 | 1e5eeff | 11,515 B | A | view · diff |
| v2.0 | 2026-07-23 | 53c5897 | 10,558 B | A | view · diff |
| git:20260611.1b8fae3 | 2026-06-11 | 1b8fae3 | 7,030 B | A | view · diff |
| v1.0 | 2026-05-27 | 0936740 | 7,025 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (12821 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
k-dense-ai/scientific-agent-skills · 56,497 stars · license MIT · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_4gskwbtxp2n6rpow GET https://markdownregistry.com/api/v1/resolve?ref=k-dense-ai/scientific-agent-skills/matchms GET https://markdownregistry.com/api/v1/blob/1bde0e20f69f99dfa44800b9e908b0f90aa1256cfdb1d88a36ed0b8064c447ec
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
More from k-dense-ai/scientific-agent-skills
Every file in k-dense-ai/scientific-agent-skills