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molecular-cloning

Molecular cloning simulation and design. PCR amplicon prediction, restriction enzyme digestion, Golden Gate and Gibson assembly simulation, primer design, CRISPR sgRNA design, and plasmid annotation. For protein-level sequence analysis use biopython or esm; for database lookups use gene-database or ensembl-database.

56

Quality

71%

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tessl review fix ./backend/cli/skills/biology/molecular-cloning/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

61%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.

A highly actionable body with concrete, executable code for every capability, but it functions as a monolith: ~500 lines of inline implementations that duplicate five orphaned scripts the reader is never told about. Adding validation checkpoints to the workflows and wiring the body to the existing bundle would address the main weaknesses.

Suggestions

Reference the existing scripts (e.g., 'CLI tools: scripts/simulate_pcr.py, scripts/restriction_digest.py, scripts/golden_gate.py, scripts/design_primers.py, scripts/design_crispr.py') and trim the inline implementations to short usage examples so the bundle files are discoverable and the body shrinks.

Add explicit validation checkpoints to the workflows, e.g., after a Golden Gate design, re-run the in-silico digest of the assembled product to verify overhang uniqueness and part order.

De-duplicate the Overview paragraph, which restates the frontmatter description almost verbatim.

DimensionReasoningScore

Conciseness

The prose sections (When to Use, Best Practices, Troubleshooting) are lean and assume competence, but the body inlines ~500 lines of full function implementations (find_primer_binding, restriction_digest, design_golden_gate, design_crispr_guides, score_guide, annotate_plasmid) even though equivalent CLI tools already exist in scripts/ — a large duplication that could be trimmed to short usage examples. Mostly efficient in tone, but the whole could be significantly tightened by leaning on the bundle.

3 / 5

Actionability

Every capability ships as complete, copy-paste-ready Python with concrete inputs and expected outputs (Quick Start runs standalone; each core capability includes runnable example invocations like the BamHI/EcoRI double digest). Not a 4 because the examples cover the common cases and require no assembly beyond pasting.

5 / 5

Workflow Clarity

The 'Typical Workflows' section lists three worked examples and Troubleshooting provides error recovery, and design_golden_gate does validate overhang compatibility inline. But the workflows are single-shot demonstration snippets with no explicit validation checkpoints (e.g., no verify-the-assembly-by-in-silico-re-digestion step after design), leaving the sequence present with checkpoints only implicit.

3 / 5

Progressive Disclosure

The bundle provides five purpose-built scripts (simulate_pcr.py, restriction_digest.py, golden_gate.py, design_primers.py, design_crispr.py) that duplicate the body's inline implementations, yet SKILL.md never references scripts/, references/, or assets/ anywhere — content that clearly belongs in the existing separate files is inlined and the bundle files are orphaned. Section headers within the body are decent, but the file split is broken, matching the anchor for inlined content with no functioning navigation to the bundle.

2 / 5

Total

13

/

20

Passed

Description

71%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, domain-rich description with excellent natural trigger terminology for molecular cloning. Its main weakness is the missing explicit 'Use when...' clause — the only conditional guidance redirects users to other skills rather than stating when this one applies.

Suggestions

Add an explicit trigger clause, e.g., 'Use when the user wants to simulate PCR or restriction digests, design primers, plan Golden Gate/Gibson assemblies, design CRISPR sgRNAs, or annotate plasmids.'

Include common synonyms and file formats in the trigger terms (e.g., 'digest', 'guide RNA', 'GenBank/.gb plasmid maps') to lift trigger-term coverage from good to comprehensive.

DimensionReasoningScore

Specificity

Lists seven concrete actions — 'PCR amplicon prediction, restriction enzyme digestion, Golden Gate and Gibson assembly simulation, primer design, CRISPR sgRNA design, and plasmid annotation' — which comprehensively cover the molecular-cloning domain. Not a 4 because there is no meaningful gap in capability coverage; every listed action is specific and executable-sounding.

5 / 5

Completeness

The 'what' is clearly and comprehensively stated, but there is no 'Use when...' clause or equivalent explicit trigger guidance; the final sentence ('For protein-level sequence analysis use biopython or esm; for database lookups use gene-database or ensembl-database') is a redirect to other skills, not a statement of when to use this one. Per the rubric guideline, a missing 'Use when...' clause caps completeness at 3.

3 / 5

Trigger Term Quality

Strong natural terms users would actually say: 'PCR', 'primer design', 'Golden Gate', 'Gibson assembly', 'CRISPR sgRNA', 'plasmid', 'restriction enzyme digestion'. Not a 5 because a few natural variations and file formats are missing (e.g., 'digest' alone, 'guide RNA', 'cloning map', '.gb'/GenBank), leaving keyword coverage good but not fully comprehensive.

4 / 5

Distinctiveness Conflict Risk

Clear niche with distinctive domain triggers (Golden Gate, Gibson, sgRNA design) and explicit redirects that sharpen boundaries against 'biopython', 'esm', 'gene-database', and 'ensembl-database'. Not a 5 because this skill is built on Biopython, so a request phrased around 'biopython' for cloning tasks carries minor overlap risk with the biopython skill itself.

4 / 5

Total

16

/

20

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

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (666 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/molecular-cloning/SKILL.md

Reviewed

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