labarchive-integration
Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes. Optional bundled scripts can be used to collect or validate source notebook data before writing.
61
72%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/Academic Writing/labarchive-integration/SKILL.mdQuality
Discovery
82%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 with excellent specificity and distinctiveness, clearly naming the input sources (LabArchives, ELN exports) and multiple concrete output types (Methods sections, data-availability statements, etc.). The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill over others. The trigger terms are naturally phrased and domain-appropriate.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user mentions LabArchives, electronic lab notebooks, ELN exports, or needs to convert lab notebook data into manuscript sections.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: converting notebook data into Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes. Also mentions bundled scripts for collecting/validating source data. | 3 / 3 |
Completeness | Clearly answers 'what does this do' with detailed output types and input sources, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The when is only implied by the description of capabilities, which per the rubric caps completeness at 2. | 2 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'LabArchives', 'notebook', 'ELN', 'manuscript', 'Methods sections', 'data-availability statements', 'reproducibility', 'experiment timelines', 'submission'. These cover the domain well and match how researchers would phrase requests. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific combination of LabArchives/ELN as input source and manuscript-ready academic writing as output. This niche is unlikely to conflict with general writing or general data processing skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
62%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured skill with a clear workflow, strong safety boundaries, and explicit validation checkpoints. Its main weaknesses are the lack of concrete input/output examples showing what notebook data and resulting academic writing look like, and some redundancy across sections. The references to bundle files that don't exist also weaken the progressive disclosure score.
Suggestions
Add at least one concrete example showing sample notebook input data and the corresponding Methods draft or Data Availability Statement output, so Claude has a clear model to follow.
Consolidate overlapping sections—merge 'Academic Writing Style Rules' and 'Deterministic Rules' into a single 'Writing Constraints' section, and reduce overlap between 'When Not to Use' and the 'Refusal and Recovery Contract'.
Either provide the referenced bundle files (e.g., `assets/writing_outputs_template.md`) or inline the essential template content so the skill is self-contained.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably well-structured but includes some redundancy—e.g., the 'When to Use' and 'When Not to Use' sections overlap with the refusal contract, and the output contracts repeat information that could be consolidated. Some sections like 'Deterministic Rules' and 'Academic Writing Style Rules' could be merged. However, it largely avoids explaining concepts Claude already knows. | 2 / 3 |
Actionability | The skill provides concrete script commands and a clear refusal template, but the core writing guidance remains somewhat abstract—there are no concrete input/output examples showing what notebook data looks like and what the resulting Methods draft or Data Availability Statement should look like. The output contracts specify what 'must include' but lack illustrative examples. | 2 / 3 |
Workflow Clarity | The five-step workflow is clearly sequenced with explicit validation at step 1 (authorization and source sufficiency), a safety pass at step 5 (claim-to-evidence mapping), and a well-defined refusal/recovery contract for when the workflow cannot proceed. The feedback loop for script failures is also addressed. The completion checklist reinforces the validation steps. | 3 / 3 |
Progressive Disclosure | The skill references external files like `assets/writing_outputs_template.md` and bundled scripts, but no bundle files are provided, making it impossible to verify these references. The SKILL.md itself is somewhat long (~170 lines of substantive content) and could benefit from splitting the detailed output contracts and style rules into separate referenced files. The structure within the file is good but the content is borderline monolithic. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- aipoch/medical-research-skills
- Commit
73f6514
- Reviewed
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