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.

Quality

78%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./skills/benchling-integration/SKILL.md

Quality

Content

72%

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

The content is highly actionable with executable code and a well-structured progressive-disclosure layer pointing to real reference files. It is held back by minor redundant prose and missing validation/feedback loops in its batch and destructive-operation workflows.

Suggestions

Remove or trim the 'Key Operations' bullet lists that restate the preceding code blocks, and tighten the overview sentence on line 15, to reduce redundancy and lift conciseness toward the score-3 anchor.

Add explicit validation feedback loops to the batch/destructive Common Use Cases (e.g., verify each bulk-imported entity with get_by_id, and validate workflow task state after auto-completion) so workflow_clarity can reach score 3.

Consolidate the version-specific notes (e.g., the 600-second max_wait_seconds parenthetical) into a single 'version notes' or 'deprecated' section rather than scattering them inline, which the rubric flags as a conciseness cost.

Dimension	Reasoning	Score
Conciseness	Mostly efficient and code-driven, but includes redundant prose Claude already knows (e.g., the overview sentence on line 15 and repeated 'Key Operations' bullet lists that restate the preceding code), fitting the 'mostly efficient but could be tightened' anchor rather than the lean score-3 level.	2 / 3
Actionability	Provides many complete, import-correct, executable code blocks (e.g., `uv pip install "benchling-sdk==1.25.0"`, `DnaSequenceCreate(...)` creation, `wait_for_task(...)`) that are copy-paste ready, matching the 'fully executable code/commands' anchor.	3 / 3
Workflow Clarity	The EventBridge setup flow and credential verification checkpoint are sequenced, but batch/destructive operations (bulk entity import, workflow auto-completion, inventory transfers) lack validation feedback loops; per the rubric, missing validation in batch operations caps this at the score-2 'validation gaps' anchor.	2 / 3
Progressive Disclosure	The body is a concise overview with clearly signaled one-level references to authentication.md, sdk_reference.md, api_endpoints.md, and eventbridge.md (all verified to exist), plus a Resources section describing each, matching the 'clear overview with well-signaled one-level-deep references' anchor.	3 / 3
	Total	10 / 12 Passed

Description

85%

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 complete, explicitly covering both capabilities and a 'Use when' trigger with a clear Benchling-specific niche. Its main weakness is trigger-term coverage, which leans on product names rather than the broader natural language a user might actually say.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete capability areas — 'registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries' — matching the 'lists multiple specific concrete actions' anchor rather than the score-2 'some actions' anchor.	3 / 3
Completeness	Explicitly answers what ('integration for registry entities, inventory, ELN entries...') and when ('Use when automating lab data with benchling-sdk or the v2 API.'), matching the 'clearly answers both what AND when with explicit triggers' anchor.	3 / 3
Trigger Term Quality	Has a 'Use when automating lab data with benchling-sdk or the v2 API' clause with product-specific keywords, but lacks broader natural variations (e.g., 'Benchling', 'sequences', 'samples') a user would commonly say, fitting the 'some relevant keywords but missing common variations' anchor.	2 / 3
Distinctiveness Conflict Risk	The Benchling-specific niche ('Benchling Python SDK and REST API integration') with distinct benchling-sdk/v2 API triggers makes it unlikely to conflict with other skills, matching the 'clear niche with distinct triggers' anchor.	3 / 3
	Total	11 / 12 Passed

Validation

81%

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 — 13 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (533 lines); consider splitting into references/ and linking	Warning
metadata_field	'metadata' should map string keys to string values	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Repository: K-Dense-AI/scientific-agent-skills
Path: skills/benchling-integration/SKILL.md
Commit: 757b63b

Reviewed: about 12 hours ago

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