Knowledge Work Plugins is an open-source collection of Claude extensions organized around roles such as productivity, sales, and customer support. Each plugin combines role-specific guidance, connectors, commands, and sub-agents so knowledge workers can use Claude with their team’s tools and processes. The catalogue entries are examples of, or workflows from, this plugin collection.
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 skills add anthropics/knowledge-work-plugins --skill instrument-data-to-allotropegit clone --depth 1 https://github.com/anthropics/knowledge-work-pluginsWrote 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/skills/anthropics/knowledge-work-plugins/instrument-data-to-allotrope)<a href="https://agentmods.dev/skills/anthropics/knowledge-work-plugins/instrument-data-to-allotrope"><img src="https://agentmods.dev/badge/skills/anthropics/knowledge-work-plugins/instrument-data-to-allotrope/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/skills/anthropics/knowledge-work-plugins/instrument-data-to-allotrope"><img src="https://agentmods.dev/badge/skills/anthropics/knowledge-work-plugins/instrument-data-to-allotrope.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00123 | $0.02419 |
| Opus 5 | $0.00062 | $0.01210 |
| Sonnet 5 | $0.00025 | $0.00484 |
| Haiku 4.5 | $0.00012 | $0.00242 |
Grade A, and why
instrument-data-to-allotrope 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 9d 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- instrument-data-to-allotrope — 100% identical, 0 lines differ
- instrument-data-to-allotrope — 100% identical, 9 lines differ
- instrument-data-to-allotrope — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instrument Data to Allotrope Converter
Convert instrument files into standardized Allotrope Simple Model (ASM) format for LIMS upload, data lakes, or handoff to data engineering teams.
Note: This is an Example Skill
This skill demonstrates how skills can support your data engineering tasks—automating schema transformations, parsing instrument outputs, and generating production-ready code.
To customize for your organization:
- Modify the
references/files to include your company's specific schemas or ontology mappings- Use an MCP server to connect to systems that define your schemas (e.g., your LIMS, data catalog, or schema registry)
- Extend the
scripts/to handle proprietary instrument formats or internal data standardsThis pattern can be adapted for any data transformation workflow where you need to convert between formats or validate against organizational standards.
Workflow Overview
- Detect instrument type from file contents (auto-detect or user-specified)
- Parse file using allotropy library (native) or flexible fallback parser
- Generate outputs:
- ASM JSON (full semantic structure)
- Flattened CSV (2D tabular format)
- Python parser code (for data engineer handoff)
- Deliver files with summary and usage instructions
When Uncertain: If you're unsure how to map a field to ASM (e.g., is this raw data or calculated? device setting or environmental condition?), ask the user for clarification. Refer to
references/field_classification_guide.mdfor guidance, but when ambiguity remains, confirm with the user rather than guessing.
Quick Start
# Install requirements first
pip install allotropy pandas openpyxl pdfplumber --break-system-packages
# Core conversion
from allotropy.parser_factory import Vendor
from allotropy.to_allotrope import allotrope_from_file
# Convert with allotropy
asm = allotrope_from_file("instrument_data.csv", Vendor.BECKMAN_VI_CELL_BLU)
Output Format Selection
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- LICENSE.txt 10 KB
- references/asm_schema_overview.md 6.0 KB
- references/field_classification_guide.md 17 KB
- references/flattening_guide.md 7.3 KB
- references/supported_instruments.md 5.2 KB
- requirements.txt 811 B
- scripts/convert_to_asm.py 17 KB runs code
- scripts/export_parser.py 14 KB runs code
- scripts/flatten_asm.py 7.2 KB runs code
- scripts/validate_asm.py 36 KB runs code
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.
- 9d ago First seen · 281 lines · 123 tokens per session scan A 6167bf1731e5
instrument-data-to-allotrope is a skill published in the GitHub repository anthropics/knowledge-work-plugins (23,938 stars, last pushed today), licensed Apache-2.0. It adds 123 tokens to every session and 2,419 once invoked, about $0.0006 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.
Other skills, from other repositories
clinical-case-report
Structured medical case presentation for clinical rounds, conferences, and documentation. Generates SOAP-format or narrative case reports with physiologically accurate vitals, labs, and evidence-based plans. Use when the brief mentions "case report", "case presentation", "SOAP note", "clinical case", "ward rounds"…
pydicom
Use pydicom to read, inspect, write, transform, and safely preflight local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.
nature-experiment-log
A workflow for turning experiment notes, images, audio, or text into structured Markdown laboratory logs with YAML metadata. It can also organize raw attachments and optionally connect the logs to Feishu or Obsidian.
nature-paper2ppt
A workflow for turning a scientific paper, preprint, PDF, article, figure legends, or reading notes into a complete Chinese PowerPoint presentation. It is designed for journal clubs, group meetings, thesis seminars, conferences, defences, and paper-sharing talks.
structuring-radiology-reports
Converts free-text radiology narratives into structured findings and impression — with measurements, laterality, anatomy, and follow-up recommendations — after OpenMed NER. Use when the user has a CT/MRI/X-ray/ultrasound/mammography report and needs the sections split (technique, comparison, findings, impression)…
parsing-ccda-documents
Parses C-CDA / CCD XML clinical documents to extract human-readable section narrative plus coded entries, keyed by section LOINC codes and templateIds. Use before OpenMed processing when ingesting C-CDA R2.1 documents (CCD, Discharge Summary, H&P, Consultation Note) exported from an EHR and you need the narrative…