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ginkgo-cloud-lab

Guides protocol selection, input preparation, pricing checks, and browser ordering on Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio). Applies to cell-free, E. coli, and Pichia protein expression; HiBiT, A280, and LabChip readouts; IVT mRNA/circRNA synthesis; thermal shift assays; Echo-MS methods; SPR target onboarding; plate-reader assay onboarding; and fluorescent pixel art.

67

Quality

84%

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SKILL.md
Quality
Evals
Security

Quality

Content

78%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 well-structured, information-dense skill body: exhaustive but tabular catalog coverage, actionable ordering steps with explicit validation and anti-assumption cautions, and exemplary one-level-deep progressive disclosure across 18 reference files. The main weaknesses are minor: no post-submission error-recovery loop and a somewhat long inline citation procedure.

Suggestions

Trim or move the arXiv citation-fetching procedure into a small reference file to keep the main body lean.

Add a short post-order verification loop (e.g., check order acknowledgment email/page for status, and what to do if the order is rejected or the template mismatches) to close the workflow's feedback-loop gap.

DimensionReasoningScore

Conciseness

The body is dense and domain-specific — protocol tables, a goal-to-protocol decision list, and ordering steps — with essentially no explanation of concepts Claude already knows. It falls short of the lean anchor at 5 mainly due to the ~15-line citation procedure (arXiv fetch-and-verify instructions) and catalog-snapshot date handling (2026-09-30), time-sensitive detail that sits in the main body rather than a reference or staleness note. It is well above the score-3 anchor, which expects unnecessary explanation; none is present. This matches the score-4 anchor: efficient, with minor instances that could be trimmed.

4 / 5

Actionability

Guidance is concrete for a browser-storefront skill: numbered steps with exact URLs ('Select a protocol at https://cloud.ginkgo.bio/protocols', 'Download the template linked on that protocol page'), a Choosing-a-Protocol list mapping goals to named protocols with prices, and explicit artifact-preservation instructions. It does not reach the fully-executable anchor because several steps deliberately defer to external pages ('inspect its actual format and fields', 'Configure parameters') rather than providing field-level detail — an honest but incomplete level of specificity. It clearly exceeds the score-3 anchor: no pseudocode-vague directions, and per the scoring notes, absence of code in an instruction-only skill is not penalized.

4 / 5

Workflow Clarity

The ordering workflow is a clear 5-step sequence with real validation checkpoints: recheck the live catalog page and configured quote before ordering, inspect the downloaded template's actual fields, review the service terms, and explicit what-does-not-count-as-confirmation cautions ('an added cart item is not an accepted or executed run', 'A feasibility report or quote is not evidence that execution has started'). It falls short of the score-5 anchor because there is no true validate->fix->retry feedback loop after submission (e.g., what to do on a rejected order beyond 'use the official contact page'), leaving minor validation gaps per the score-4 anchor.

4 / 5

Progressive Disclosure

The body is a genuine overview — catalog tables linking each of 18 protocols to its own references/*.md file (all verified to exist), with categorized sections, selection guidance, and ordering policy inline. References are one level deep, clearly signaled by category, and the per-protocol detail (inputs, outputs, workflow, ordering) is appropriately split into the reference files. This matches the anchor 'Clear overview with well-signaled one-level-deep references; content appropriately split; easy navigation' exactly.

5 / 5

Total

17

/

20

Passed

Description

83%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 strong, specific description in correct third-person voice that names concrete actions, the platform, and nearly the full service scope. Its main gap is the absence of an explicit 'Use when...' trigger clause, and a few natural trigger terms (purification, in vitro transcription) are missing.

Suggestions

Add an explicit trigger clause, e.g. 'Use when ordering or planning runs on Ginkgo Cloud Lab, or when the user mentions Ginkgo Bioworks, cloud.ginkgo.bio, or any of these protocols.'

Include 'purification' (express+purify tiers) and 'in vitro transcription' as an IVT synonym to broaden natural trigger coverage.

DimensionReasoningScore

Specificity

The description lists four concrete actions — "Guides protocol selection, input preparation, pricing checks, and browser ordering" — and then comprehensively enumerates the covered service scope ("cell-free, E. coli, and Pichia protein expression; HiBiT, A280, and LabChip readouts; IVT mRNA/circRNA synthesis; thermal shift assays; Echo-MS methods; SPR target onboarding; plate-reader assay onboarding; and fluorescent pixel art"). This matches the anchor 'Lists multiple specific concrete actions; comprehensive coverage' rather than the score-4 anchor, which expects minor gaps in coverage — nearly every catalog category is named. Third-person voice ('Guides') is used correctly.

5 / 5

Completeness

The 'what' is explicit and concrete (protocol selection, input preparation, pricing checks, browser ordering on Cloud Lab). A 'when' is present via the "Applies to..." clause enumerating the exact service domains, so the missing-'Use when' cap at 3 does not apply — this is equivalent explicit trigger guidance. It falls short of the score-5 anchor because there is no direct 'Use when...' phrasing tied to user requests (e.g. 'Use when the user wants to order or plan a Cloud Lab run'), leaving the trigger slightly less explicit than the anchor's 'concrete trigger phrases'.

4 / 5

Trigger Term Quality

Strong natural domain keywords are present: "protein expression", "cell-free", "E. coli", "mRNA", "circRNA", "thermal shift", "SPR", "plate-reader assay", and the platform name "Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio)". A few natural terms a user would say are missing, e.g. "purification" (the catalog's express+purify tiers), "in vitro transcription" as a synonym for IVT, and "binding affinity". This fits the anchor 'Good keyword coverage; a few natural terms missing' rather than the comprehensive-with-synonyms anchor at 5.

4 / 5

Distinctiveness Conflict Risk

The description names a unique platform — "Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio)" — plus vendor-specific readout technologies (HiBiT, LabChip, Echo-MS), creating a clear niche with distinct triggers and minimal conflict risk with any other skill. This clearly matches the score-5 anchor; no neighboring anchor fits better.

5 / 5

Total

18

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

K-Dense-AI/scientific-agent-skills

Path

skills/ginkgo-cloud-lab/SKILL.md

Reviewed

Table of Contents

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