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benchling-integration

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

Quality

68%

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SecuritybySnyk

Passed

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tessl review fix ./skills_all/benchling-integration/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

53%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 delivers strong, executable SDK guidance across registry, inventory, notebook, and workflow domains, with real imports and runnable patterns. However, its progressive disclosure architecture is broken — every referenced references/*.md file and the claimed scripts/ are absent from the bundle while their content is inlined — and batch workflows lack validation checkpoints. The Events and Data Warehouse sections read as capability marketing rather than actionable instruction.

Suggestions

Create the referenced files (references/authentication.md, references/sdk_reference.md, references/api_endpoints.md) or remove the citations — as shipped, every 'refer to' pointer dead-ends and scripts/ does not exist.

Move the per-entity SDK patterns (registry, inventory, notebook, workflows) into references/sdk_reference.md and keep SKILL.md as a lean overview with quick-start examples, which would also fix the ~470-line token load.

Add validation and error-recovery steps to the batch workflows (e.g., per-record try/except with a failure log during FASTA import, verify created counts after bulk import) to lift workflow clarity past the batch-operation cap.

Either give the Data Warehouse and Events sections concrete, executable content (connection string setup, an EventBridge rule example) or cut them to one-line pointers in a reference file.

DimensionReasoningScore

Conciseness

Mostly efficient SDK-specific material, but it includes unnecessary explanation and padding: content-free bullet lists ('Common Queries: Aggregate experimental results / Analyze inventory trends'), a conceptual Events section with no code, obvious security advice ('Never commit API keys to version control'), and a scripts/ section that only notes it contains removable example scripts. This matches 'mostly efficient but includes some unnecessary explanation or could be tightened'; not 4 because several sections could be cut wholesale.

3 / 5

Actionability

The body is full of executable, import-complete Python covering the common cases (entity CRUD, registration with naming_strategy, pagination, wait_for_task, CSV export), matching 'mostly executable guidance; concrete code or commands with minor gaps'. Not 5 because the Data Warehouse and Events sections provide no concrete commands or connection examples; not 3 because the code is genuinely executable rather than pseudocode.

4 / 5

Workflow Clarity

Multi-step sequences are present and readable (bulk FASTA import, inventory audit, bulk task updates, export), but the batch workflows have no validation or verification steps (e.g., no error handling around per-record creates, no post-import count check), which caps workflow clarity at 3 per the batch-operations rule. Not 2 because steps are coherent and well-ordered; not 4 because checkpoints are absent, not just implicit.

3 / 5

Progressive Disclosure

The body instructs 'refer to references/authentication.md', 'references/sdk_reference.md', and 'references/api_endpoints.md' and lists them in Resources, but none of these files exist in the bundle (references/ and scripts/ directories are absent), so navigation is dead-ended. Meanwhile ~470 lines of per-entity SDK reference material are inlined in SKILL.md itself — the situation the 'content that clearly belongs in separate files is inlined' anchor describes. Not 3 because the references are not merely unclear, they are missing, breaking the disclosure structure entirely; not 1 because the body is well-sectioned with headers and references are only one level deep.

2 / 5

Total

12

/

20

Passed

Description

70%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 and unmistakably scoped to the Benchling platform, listing most of its capability areas concretely. Its main weakness is the absence of any explicit 'Use when...' trigger clause, leaving the activation guidance implicit. A few natural synonyms (notebook, sequences, plasmids, SDK) would strengthen trigger coverage.

Suggestions

Add an explicit trigger clause, e.g., 'Use when working with Benchling, the Benchling API or Python SDK, or when managing lab registry entities, inventory, or notebook entries.'

Swap the vague tail 'for lab data management automation' for concrete terms, and add natural synonyms users would say such as 'notebook', 'sequences', 'plasmids', and 'Python SDK'.

Spell out 'ELN' as 'electronic lab notebook (ELN)' so the description triggers on the plain-language phrase users actually type.

DimensionReasoningScore

Specificity

Lists several concrete actions ('Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse'), matching the 'several specific actions; minor gaps' anchor. Not 5 because the trailing 'for lab data management automation' is vague padding and capability coverage has small gaps; not 3 because it goes well beyond 1-2 actions.

4 / 5

Completeness

The 'what' is clear and multi-faceted, but there is no 'Use when...' clause or equivalent explicit trigger guidance; 'for lab data management automation' only weakly implies when to use it, which caps completeness at 3 per the judging guidelines. Not 4 because the 'when' is never made explicit.

3 / 5

Trigger Term Quality

Good keyword coverage with natural terms a Benchling user would say: 'Benchling', 'registry', 'inventory', 'ELN entries', 'workflows', 'Data Warehouse', 'API'. A few natural terms are missing (e.g., 'notebook', 'sequences', 'plasmids', 'Python SDK'), so it falls just short of the comprehensive-synonyms anchor at 5 and clearly above partial coverage at 3.

4 / 5

Distinctiveness Conflict Risk

'Benchling' names a clear niche with distinct triggers (registry, ELN, Data Warehouse, Benchling Apps) and minimal overlap risk with any generic skill. It matches the 'clear niche with distinct triggers' anchor; 4 would require actual minor overlap with a closely related skill, which is not the case.

5 / 5

Total

16

/

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 2 missing

Warning

Total

15

/

16

Passed

Repository

Microck/ordinary-claude-skills

Path

skills_all/benchling-integration/SKILL.md

Reviewed

Table of Contents

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