flow-cytometry-analysis

Complete flow cytometry analysis pipeline. FCS file handling, compensation, manual/automated gating, immunophenotyping, CFSE proliferation analysis, cell cycle analysis (Dean-Jett-Fox), and apoptosis assays. Extends flowio with analytical workflows. For raw FCS parsing only use flowio.

Quality

70%

Does it follow best practices?

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tessl review fix ./backend/cli/skills/biology/flow-cytometry-analysis/SKILL.md

Quality

Content

65%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Highly actionable content with comprehensive, executable code and a well-organized section structure. The weaknesses are verbosity from inlining full implementations that duplicate the provided scripts, missing validation checkpoints in the workflows, and the failure to reference the existing bundle scripts for progressive disclosure.

Suggestions

Replace the inlined full implementations in 'Core Capabilities' with concise snippets and point to the corresponding scripts/ files (e.g., 'See scripts/cell_cycle.py for the full Dean-Jett-Fox implementation'), removing the duplication with 'Typical Workflows'.

Add explicit validation checkpoints to each workflow (e.g., verify event counts after gating, check curve-fit success before reporting cell-cycle phases, confirm compensation matrix is square and invertible) with fix-and-retry guidance.

Link the existing bundle scripts from the relevant capability sections so the detailed code is one level deep and clearly signaled.

Dimension	Reasoning	Score
Conciseness	Style is efficient (no padding explaining concepts Claude already knows), but at ~530 lines the body inlines full implementations for all 8 capabilities plus 3 workflows, with the 'Typical Workflows' sections re-calling logic already defined in 'Core Capabilities', producing noticeable redundancy that could be tightened.	3 / 5
Actionability	Fully executable, copy-paste-ready Python with complete function implementations (e.g., parse_spillover_matrix, compensate, auto_gate_gmm, dean_jett_fox, annexin_v_pi_analysis) covering the common cases with concrete thresholds and example calls.	5 / 5
Workflow Clarity	The three 'Typical Workflows' are clearly sequenced (compensate -> gate -> analyze), but they lack explicit validation checkpoints or validate-fix-retry feedback loops, and the batch-analysis context plus the rubric's missing-validation cap hold this at 3.	3 / 5
Progressive Disclosure	Section structure is clear and navigable (Overview, When to Use, Quick Start, Core Capabilities 1-8, Workflows, Best Practices, Troubleshooting, Resources), but full code implementations are inlined in SKILL.md while matching scripts/ files (cell_cycle.py, cfse_proliferation.py, gate_fcs.py, immunophenotype.py) exist yet are never referenced or linked, so content that belongs in separate files is inlined and navigation to the bundle is absent.	3 / 5
	Total	14 / 20 Passed

Description

75%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A specific, well-scoped description that concretely enumerates the pipeline's capabilities and cleanly distinguishes itself from the related flowio skill. Its main weakness is the absence of an explicit 'Use when...' trigger clause, which caps completeness.

Suggestions

Add an explicit 'Use when...' clause naming concrete trigger phrases (e.g., 'Use when analyzing multi-color flow cytometry experiments, applying compensation, building gating hierarchies, or running immunophenotyping/CFSE/cell cycle/apoptosis assays').

Include the '.fcs' file extension and common synonyms (e.g., 'fluorescence-activated cell sorting', 'FACS') to broaden natural trigger-term coverage.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions — 'FCS file handling, compensation, manual/automated gating, immunophenotyping, CFSE proliferation analysis, cell cycle analysis (Dean-Jett-Fox), and apoptosis assays' — giving comprehensive coverage of the pipeline.	5 / 5
Completeness	The 'what' is clear and detailed, but there is no 'Use when...' clause or equivalent explicit trigger guidance; 'For raw FCS parsing only use flowio' is a boundary/disambiguation, not a when-to-use trigger, so completeness is capped at 3 per the rubric guideline.	3 / 5
Trigger Term Quality	Strong natural keywords ('flow cytometry', 'FCS file', 'gating', 'immunophenotyping', 'CFSE proliferation', 'apoptosis') but missing the '.fcs' file extension and a few common synonyms, so just short of comprehensive.	4 / 5
Distinctiveness Conflict Risk	Clear niche ('Complete flow cytometry analysis pipeline') with an explicit disambiguation from flowio ('For raw FCS parsing only use flowio'), giving minimal conflict risk with other skills.	5 / 5
	Total	17 / 20 Passed

Validation

81%

Warnings & errors only

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 (540 lines); consider splitting into references/ and linking	Warning
metadata_version	'metadata.version' is missing	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Repository: synthetic-sciences/openscience
Path: backend/cli/skills/biology/flow-cytometry-analysis/SKILL.md
Commit: 3a6c3a9

Reviewed: 1 day ago

Table of Contents

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