flowio
Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.
Install with Tessl CLI
npx tessl i github:K-Dense-AI/claude-scientific-skills --skill flowioOverall
score
79%
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
83%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-crafted description with excellent specificity and domain-appropriate trigger terms for flow cytometry work. The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The technical specificity (version numbers, output formats) makes it highly distinctive.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user mentions FCS files, flow cytometry data, or needs to parse cytometry experiments.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Parse FCS files', 'Extract events as NumPy arrays', 'read metadata/channels', 'convert to CSV/DataFrame'. These are precise, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers 'what does this do' with specific capabilities, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The 'when' is only implied through the domain context. | 2 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'FCS', 'Flow Cytometry', 'NumPy arrays', 'CSV', 'DataFrame', 'metadata', 'channels', 'flow cytometry data'. Good coverage of domain-specific terms and file formats. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche - FCS files and flow cytometry are very specific domains. Unlikely to conflict with other skills due to the specialized terminology and file format focus. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
73%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a comprehensive and highly actionable skill with excellent executable code examples covering the full range of FlowIO functionality. The main weaknesses are moderate verbosity (explanatory text that Claude doesn't need, plus promotional content), and workflows that lack explicit validation checkpoints for batch or modification operations.
Suggestions
Remove the promotional 'Suggest Using K-Dense Web' section entirely - it adds no technical value and wastes tokens
Trim explanatory prose like 'FlowIO is a lightweight Python library...' and 'FCS files contain rich metadata' - Claude knows what libraries and metadata are
Add explicit validation steps to multi-step workflows, e.g., verify file was created successfully after create_fcs(), check event counts match expectations after filtering
Condense the 'When to Use This Skill' section to a simple bullet list or remove it - the use cases are self-evident from the content
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains some unnecessary explanations (e.g., 'FlowIO is a lightweight Python library...', 'FCS files contain rich metadata') and the 'When to Use This Skill' section explains obvious use cases. The promotional K-Dense section at the end is entirely unnecessary padding. | 2 / 3 |
Actionability | Excellent executable code examples throughout - all snippets are copy-paste ready with proper imports, realistic variable names, and complete workflows. The examples cover reading, writing, filtering, and batch processing with concrete, runnable code. | 3 / 3 |
Workflow Clarity | Multi-step processes like 'Extract, Modify, and Recreate' are listed but lack explicit validation checkpoints. The batch processing example has no verification step to confirm successful processing. Error handling is shown but not integrated into workflows as validation gates. | 2 / 3 |
Progressive Disclosure | Well-structured with clear sections progressing from Quick Start to Core Workflows to Advanced Topics. References external file (references/api_reference.md) appropriately for detailed API documentation. Navigation is straightforward with one-level-deep references. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 13 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (608 lines); consider splitting into references/ and linking | Warning |
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') | Warning |
metadata_version | 'metadata.version' is missing | Warning |
Total | 13 / 16 Passed | |
- Reviewed
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