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bids

Organizes, queries, validates, and converts Brain Imaging Data Structure (BIDS) datasets. Supports organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives.

64

Quality

81%

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SKILL.md
Quality
Evals
Security

Quality

Content

78%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.

A well-structured overview skill: the body carries high-value, hard-to-rediscover BIDS knowledge and reliably points to real, one-level-deep bundle files for worked code. The main residual improvements are de-duplicating repeated mentions (bids-examples, BEP032) and making validate-fix-retry loops explicit inside the workflow steps.

DimensionReasoningScore

Conciseness

The body is dense with genuinely non-obvious, skill-specific knowledge (validator flag differences, slice-timing recovery, i/j/k axis conventions, PyBIDS index caching) and avoids tutorial-style padding about what MRI or JSON is. Minor trimmable redundancy — bids-examples appears in Best Practices #11, the tool table, and Documentation; BEP032 is introduced in the Overview and repeated in the BEPs section — keeps it below the lean 'every token earns its place' anchor.

4 / 5

Actionability

Concrete, executable guidance dominates: exact install commands, a runnable PyBIDS caching snippet (`BIDSLayout("/data", database_path="/cache/pybids")`), a minimal `dataset_description.json` literal, and specific validator invocations with flags (`--format json --max-rows -1 --outfile`). It is not a 5 because the most common copy-paste workflows (PyBIDS queries, conversion commands) live in references/core_workflows.md rather than inline, leaving small gaps in the body itself.

4 / 5

Workflow Clarity

The twelve workflow areas are enumerated with a clear delegation to worked code, conversion follows an explicit reconnaissance → heuristic → convert sequence, and validation checkpoints are emphasized ("Validate early and often", "Run the BIDS validator after every conversion or modification. Fix errors before they compound", plus the warning that successful PyBIDS indexing is not compliance). It falls short of 5 because the validate → fix → re-validate feedback loop is stated as advice rather than woven into each workflow's numbered steps.

4 / 5

Progressive Disclosure

SKILL.md is a genuine overview: twelve workflow areas are summarized one-to-two lines each and delegated to references/core_workflows.md, the Reference Materials section describes all six bundled files, and every referenced path (core_workflows.md, beps.yml, bids_schema.json, scripts/update_schema.py) exists in the bundle. References are one level deep — core_workflows.md links to real bundled files and external URLs, not to further instruction files — so navigation matches the clear-overview anchor exactly.

5 / 5

Total

17

/

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.

A specific, well-scoped description in third person with concrete verbs and rich domain keywords. Its one structural weakness is the absence of an explicit 'Use when...' trigger clause, which caps completeness and leaves activation guidance implicit.

Suggestions

Append an explicit trigger clause, e.g. "Use when working with BIDS datasets, converting DICOM scans to BIDS, or preparing data for OpenNeuro or DANDI."

Add natural synonyms and extensions users actually mention — NIfTI (.nii.gz), EEG (.edf), heudiconv, bids-validator — to broaden trigger coverage.

Trim the parenthetical modality list (11 modalities) to the most common triggers; the full list can live in the body, keeping the description tight.

DimensionReasoningScore

Specificity

The description lists multiple concrete third-person actions — "Organizes, queries, validates, and converts" BIDS datasets, "converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives" — with comprehensive coverage of the skill's capability areas. This matches the anchor for multiple specific concrete actions; nothing is left at the abstract 'helps with data' level.

5 / 5

Completeness

The 'what' is explicit and thorough (organize, query, validate, convert, write sidecars, create derivatives), but there is no 'Use when...' clause or equivalent explicit trigger guidance — the 'when' is only weakly implied by the enumerated activities. Per the judging guidelines, a missing explicit trigger clause caps completeness at 3; it is not a 2 because the 'what' is far from vague, and not a 4+ because no 'when' guidance is stated at all.

3 / 5

Trigger Term Quality

Strong natural keywords: "BIDS", the full expansion "Brain Imaging Data Structure", "DICOM", and modality names (MRI, EEG, MEG, PET, microscopy, EMG) that users would naturally say. A few natural trigger terms are missing — file extensions (.nii.gz, .edf) and tool/repository names users commonly mention (NIfTI, OpenNeuro, DANDI, heudiconv) — so it falls just short of the comprehensive synonym-and-extension anchor.

4 / 5

Distinctiveness Conflict Risk

"Brain Imaging Data Structure (BIDS)" plus "DICOM to BIDS" occupy a clear niche with distinct triggers; virtually no other skill would compete for these phrases. It is not a 4 because the modality enumeration and BIDS-specific terminology leave essentially no overlap risk with generic data-organization skills.

5 / 5

Total

17

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

K-Dense-AI/scientific-agent-skills

Path

skills/bids/SKILL.md

Reviewed

Table of Contents

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