opentrons-integration
Official Opentrons Protocol API for OT-2 and Flex robots. Use when writing protocols specifically for Opentrons hardware with full access to Protocol API v2 features. Best for production Opentrons protocols, official API compatibility. For multi-vendor automation or broader equipment control use pylabrobot.
76
70%
Does it follow best practices?
Impact
85%
1.11xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/opentrons-integration/SKILL.mdQuality
Discovery
89%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong description that clearly identifies its niche (Opentrons Protocol API), provides explicit 'Use when' guidance, and proactively distinguishes itself from a related skill (pylabrobot). Its main weakness is that it could list more specific concrete actions (e.g., pipetting, labware management, module control) rather than broadly referencing 'Protocol API v2 features'.
Suggestions
Add specific concrete actions the skill enables, such as 'pipette liquids, define labware, control temperature/magnetic modules, manage deck layouts' to improve specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Opentrons Protocol API, OT-2 and Flex robots) and mentions 'writing protocols' and 'Protocol API v2 features', but does not list specific concrete actions like 'pipette liquids, manage labware, control temperature modules'. | 2 / 3 |
Completeness | Clearly answers both what ('Official Opentrons Protocol API for OT-2 and Flex robots') and when ('Use when writing protocols specifically for Opentrons hardware with full access to Protocol API v2 features'). Also includes explicit negative trigger guidance distinguishing from pylabrobot. | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms users would say: 'Opentrons', 'OT-2', 'Flex', 'Protocol API', 'Protocol API v2', 'production Opentrons protocols'. Also distinguishes from 'pylabrobot' for multi-vendor scenarios, which helps with routing. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with clear niche (Opentrons-specific hardware protocols) and explicitly differentiates from a competing skill (pylabrobot for multi-vendor automation), making conflict very unlikely. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is a comprehensive but excessively verbose API reference masquerading as a skill file. While the code examples are excellent and fully executable, the content fails to respect token budget by documenting nearly every API method inline rather than splitting reference material into separate files. The lack of validation checkpoints in multi-step workflows (PCR, serial dilution) is a notable gap given the destructive nature of physical robot operations.
Suggestions
Move detailed API reference content (well access methods, module control commands, flow rate settings) to a separate reference file and keep only 1-2 complete protocol examples in SKILL.md
Remove the 'When to Use This Skill' section entirely and trim 'Best Practices' and 'Troubleshooting' to only non-obvious, Opentrons-specific guidance
Add explicit validation steps to protocol patterns: run simulation check, verify deck layout, confirm tip count before execution
Cut sections that document standard Python API patterns Claude can infer (basic aspirate/dispense/pick_up_tip, well indexing) and focus on Opentrons-specific gotchas and constraints
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~400+ lines. Extensively documents basic API patterns Claude already knows or can infer from minimal examples. Sections like 'Well Access Methods', 'Location Methods', basic operations (pick_up_tip, aspirate, dispense) are standard API usage that don't need exhaustive documentation. The 'When to Use This Skill' section restates the obvious. Troubleshooting tips like 'check for air bubbles' and 'verify module is connected' add no value. | 1 / 3 |
Actionability | All code examples are concrete, executable Python with correct API calls, specific labware names, slot positions, and realistic parameter values. The protocol patterns (serial dilution, PCR setup, plate replication) are complete, copy-paste ready protocols. | 3 / 3 |
Workflow Clarity | The protocol patterns show clear sequences of operations, but there are no validation checkpoints. No mention of running simulation to verify before execution (despite listing it as a best practice), no error recovery steps within protocols, and no feedback loops for catching issues during multi-step operations like PCR setup or serial dilution. | 2 / 3 |
Progressive Disclosure | References to 'references/api_reference.md' and 'scripts/' directory exist, but the SKILL.md itself is a monolithic wall of content that should have been split. The exhaustive API documentation (module control, well access, liquid handling) belongs in reference files, with only quick-start patterns in the main file. | 2 / 3 |
Total | 8 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (572 lines); consider splitting into references/ and linking | Warning |
metadata_version | 'metadata.version' is missing | Warning |
Total | 9 / 11 Passed | |
- Repository
- K-Dense-AI/claude-scientific-skills
- Commit
25e1c0f
- Reviewed
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