microbiome-diversity-reporter

Interpret Alpha and Beta diversity metrics from 16S rRNA sequencing results.

Quality

27%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./scientific-skills/Academic Writing/microbiome-diversity-reporter/SKILL.md

Quality

Discovery

40%

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

The description targets a clear and specific scientific niche (16S rRNA diversity analysis), which gives it strong distinctiveness. However, it lacks a 'Use when...' clause, limiting its completeness, and could benefit from listing more concrete actions and natural trigger terms that users in the microbiome analysis domain would use.

Suggestions

Add a 'Use when...' clause with explicit triggers, e.g., 'Use when the user asks about microbiome analysis, 16S rRNA results, diversity indices, or amplicon sequencing outputs.'

List more specific concrete actions such as 'calculate Shannon/Simpson indices, generate PCoA/NMDS plots, compare diversity across sample groups, interpret rarefaction curves.'

Include common user-facing synonyms and related terms like 'microbiome', 'OTU table', 'ASV', 'UniFrac', 'QIIME', 'amplicon' to improve trigger term coverage.

Dimension	Reasoning	Score
Specificity	Names the domain (16S rRNA sequencing) and some actions (interpret Alpha and Beta diversity metrics), but does not list multiple concrete actions such as generating plots, comparing groups, or calculating specific indices.	2 / 3
Completeness	Describes what the skill does (interpret diversity metrics) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, a missing 'Use when' clause caps completeness at 2, and since the 'what' is also only partially described, this scores a 1.	1 / 3
Trigger Term Quality	Includes relevant technical keywords like 'Alpha diversity', 'Beta diversity', '16S rRNA', and 'sequencing results', but misses common user variations such as 'microbiome', 'OTU', 'ASV', 'Shannon index', 'UniFrac', 'amplicon sequencing', or 'metagenomics'.	2 / 3
Distinctiveness Conflict Risk	The combination of '16S rRNA sequencing' with 'Alpha and Beta diversity metrics' is a very specific niche that is unlikely to conflict with other skills.	3 / 3
	Total	8 / 12 Passed

Implementation

14%

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

This skill is heavily padded with generic boilerplate sections (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria, Response Template) that are not specific to microbiome diversity analysis and waste significant token budget. While the Usage section with CLI parameters, input formats, and example JSON output provides some genuine value, the core workflow lacks domain-specific guidance for interpreting alpha and beta diversity metrics. The document structure is disorganized with circular references and duplicated content.

Suggestions

Remove all generic boilerplate sections (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria, Response Template, Output Requirements) that don't contain microbiome-specific guidance—these waste tokens on content Claude already knows.

Add domain-specific interpretation guidance: what Shannon index ranges indicate low/high diversity, how to interpret PCoA clustering, what PERMANOVA p-values mean, and common pitfalls in 16S analysis (e.g., rarefaction depth selection, compositional data issues).

Reorganize the document so Overview comes first, followed by Usage, then Input Format, then Output—and remove circular references like 'See ## Usage above'.

Add validation checkpoints specific to microbiome analysis: verify rarefaction depth adequacy, check minimum sample sizes per group for PERMANOVA, validate OTU table sparsity before proceeding.

Dimension	Reasoning	Score
Conciseness	Extremely verbose and repetitive. Contains massive amounts of boilerplate (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria, Response Template) that add no value for Claude. Multiple sections reference each other circularly ('See ## Usage above', 'See ## Workflow above'). The Workflow section is entirely generic and not specific to microbiome analysis. Much content is duplicated (e.g., py_compile appears 3+ times, --help appears twice).	1 / 3
Actionability	The Usage section provides concrete CLI commands with specific parameters, input format examples, and example JSON output, which is genuinely useful. However, the generic workflow steps (confirm objective, validate request, etc.) are vague meta-instructions rather than actionable microbiome analysis guidance. No actual executable Python code for interpreting diversity metrics is shown—only CLI invocations of a script we can't verify exists.	2 / 3
Workflow Clarity	The 'Workflow' section is entirely generic boilerplate with no microbiome-specific steps. There are no validation checkpoints for the actual analysis (e.g., checking rarefaction depth, verifying OTU table format before processing, validating PERMANOVA assumptions). The 'Example run plan' is also generic. For a skill involving scientific data analysis with potential for misinterpretation, the lack of domain-specific validation steps is a significant gap.	1 / 3
Progressive Disclosure	The document is a monolithic wall of text with poor organization. Sections appear in illogical order (Example Usage before Overview, references to '## Usage above' and '## Workflow above' that appear later in the document). References to 'references/' directory and 'references/audit-reference.md' exist but no bundle files are provided to verify. Content that could be separate (input format specs, parameter tables, response templates) is all inline.	1 / 3
	Total	5 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Repository: aipoch/medical-research-skills
Commit: 73f6514

Reviewed: 4 days ago

Table of Contents

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