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benchling-integration

Benchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. Use when automating lab data with benchling-sdk or the v2 API.

68

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

72%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.

The body is well-structured with strong progressive disclosure and mostly executable examples, but batch operations lack validation checkpoints and a few examples have minor completeness gaps.

Suggestions

Add explicit validation/verification steps to the batch use cases (e.g., confirm count of imported sequences matches input, verify exported CSV row count) to lift workflow clarity above 3.

Make code examples fully self-contained by including all referenced imports (e.g., WorkflowTaskUpdate, DnaSequenceCreate) or noting they are illustrative snippets from a larger reference.

Trim the opening overview prose that restates what Benchling is and what registry entities are, since Claude already knows these concepts.

DimensionReasoningScore

Conciseness

Mostly efficient with executable code and brief inline comments, but the overview prose restates some concepts Claude already knows and several full code blocks live in the overview rather than references.

4 / 5

Actionability

Provides concrete, executable Python across best practices and four use cases with real imports and API calls, though a few examples omit imports or rely on undefined helpers like auto_validate.

4 / 5

Workflow Clarity

Capability sections are present and sequenced, but batch operations (bulk import, bulk export, workflow updates) lack explicit validate/verify checkpoints, which caps the score per the rubric.

3 / 5

Progressive Disclosure

Clear overview with five well-signaled, one-level-deep reference files (all verified present) linked inline and enumerated in a Resources section, with detail appropriately split out of the overview.

5 / 5

Total

16

/

20

Passed

Description

92%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.

The description is specific, complete, and clearly distinguishes the skill with explicit what-and-when guidance. Minor room for improvement only in broader trigger-term synonyms.

DimensionReasoningScore

Specificity

Lists multiple concrete capability domains (registry entities, inventory, ELN entries, workflows, Benchling Apps, Data Warehouse queries) across both the Python SDK and REST API, giving comprehensive coverage.

5 / 5

Completeness

Explicitly states both what the skill does (integration for the listed capability domains via SDK/REST API) and when to use it ('Use when automating lab data with benchling-sdk or the v2 API').

5 / 5

Trigger Term Quality

Includes relevant natural terms (benchling-sdk, v2 API, lab data, registry entities, inventory, ELN, workflows), but lacks common synonyms and file extensions users might mention, leaving a few natural terms missing.

4 / 5

Distinctiveness Conflict Risk

Targets a clear, niche platform (Benchling) with distinct triggers (benchling-sdk, v2 API, lab data), so overlap with other skills is minimal.

5 / 5

Total

19

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

Total

15

/

16

Passed

Repository
K-Dense-AI/scientific-agent-skills
Reviewed

Table of Contents

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