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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.

58

Quality

68%

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SecuritybySnyk

High

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tessl review fix ./backend/cli/skills/biology/benchling-integration/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.

The body is a well-structured, code-rich integration guide with real one-level-deep references. It is held back by some conceptual padding, batch/destructive operations lacking validation feedback loops, and minor reference organization issues including a scripts/ section with no matching directory.

Suggestions

Add validation/feedback loops (verify-after-write, retry-on-failure checks) to the batch and destructive examples — bulk entity import, inventory transfers, and bulk workflow task updates — to lift workflow_clarity above the 3 cap.

Trim explanation Claude already knows (generic security boilerplate, BI-tool name lists) to tighten conciseness toward the score-4/5 anchors.

Convert reference paths to markdown links (e.g. [authentication.md](references/authentication.md)) and either create the referenced scripts/ directory or remove the scripts/ section so all signaled references resolve.

DimensionReasoningScore

Conciseness

The body is mostly efficient and code-heavy, but includes explanation Claude already knows — e.g. 'Store credentials securely (use environment variables or password managers)', generic Security Considerations bullets, and filler like 'Jupyter notebooks for interactive analysis' / 'BI tools (Tableau, Looker, PowerBI)'. Matches the score-3 anchor of mostly efficient with some unnecessary explanation; not a 4 because the padding is more than minor.

3 / 5

Actionability

Provides extensive concrete, copy-pasteable Python SDK code covering authentication, entity CRUD, inventory, notebooks, workflows, async tasks, retries, pagination, and the fields helper, matching the score-4 anchor of mostly executable guidance with minor gaps. Not a 5 because a few examples have gaps (e.g. the containers.transfer call signature appears approximate).

4 / 5

Workflow Clarity

Some sequences are clear (the Events integration pattern is a numbered 4-step list; async task handling is shown), but batch and destructive operations — 'Batch operations for bulk transfers', bulk entity import, and bulk workflow task updates — lack validation checkpoints and feedback loops. Per the rubric's scoring notes, missing feedback loops for batch/destructive operations caps workflow_clarity at 3.

3 / 5

Progressive Disclosure

Good structure with overview, when-to-use, seven capability sections, best practices, and common use cases, plus one-level-deep references to three real files (authentication.md, sdk_reference.md, api_endpoints.md — all confirmed present in references/). Matches the score-4 anchor of good structure with mostly clear references and minor organization gaps; not a 5 because references use backtick paths rather than markdown links and a documented scripts/ section has no corresponding directory.

4 / 5

Total

14

/

20

Passed

Description

75%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 highly specific and clearly distinct, naming many concrete Benchling capabilities in third person. Its main weakness is the absence of an explicit 'Use when...' trigger clause, which caps completeness at 3.

Suggestions

Add an explicit trigger clause such as 'Use when working with Benchling's API/SDK, managing biological sequences or inventory, automating lab workflows, or querying the Data Warehouse.' to raise completeness.

Include a couple of natural user-utterance phrases and synonyms (e.g. 'Benchling API', 'lab notebook', 'registry entities') to improve trigger term quality from a capability list toward user phrasing.

Keep the current concrete action list intact — it is the description's strongest dimension.

DimensionReasoningScore

Specificity

Lists multiple concrete actions across a comprehensive capability surface — 'Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse' — matching the score-5 anchor of multiple specific concrete actions with comprehensive coverage.

5 / 5

Completeness

The 'what' is clearly stated via the capability list, but there is no explicit 'Use when...' or equivalent trigger clause; the trailing 'for lab data management automation' is a purpose hint, not trigger guidance. Per the rubric, a missing 'Use when...' clause caps completeness at 3, and it is not a 4 because the 'when' is not explicit.

3 / 5

Trigger Term Quality

Good keyword coverage with natural domain terms (Benchling, registry, inventory, ELN entries, workflows, Data Warehouse, lab data management automation) but presented as a capability list rather than the natural phrases a user would utter, and missing some synonyms/extensions. Not a 5 because it is not comprehensive natural user phrasing; not a 3 because coverage is clearly stronger than a single generic keyword.

4 / 5

Distinctiveness Conflict Risk

Benchling is a specific named platform with a clear niche (life-sciences R&D), giving distinct triggers and minimal conflict risk with other skills, matching the score-5 anchor.

5 / 5

Total

17

/

20

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository
synthetic-sciences/openscience
Reviewed

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