Agent skill

Neuropsych Battery Selector

by NeuroAIHub in NeuroAIHub/BrainPilot

Domain-validated decision logic for selecting neuropsychological test batteries matched to suspected cognitive deficit profiles

AGPL-3.0Auto-check passed

Install Neuropsych Battery Selector

skills CLI
$ npx skills add NeuroAIHub/BrainPilot --skill neuropsych-battery-selector -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install NeuroAIHub/BrainPilot neuropsych-battery-selector --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/NeuroAIHub/BrainPilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/skills/skills/10_Clinical_Neuropsychology/neuropsych-battery-selector .claude/skills/neuropsych-battery-selector && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
neuropsych-battery-selector
GitHub stars
1.1k
Token cost
~4k tokens
SKILL.md length
2,008 words
Files
3 (incl. references)
Skills in repo
59
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Domain-validated decision logic for selecting neuropsychological test batteries matched to suspected cognitive deficit profiles

  • Works in 6 steps: Clarify the Referral Question → Identify Target Cognitive Domains → Assemble the Battery → …
  • SKILL.md covers Purpose, When to Use This Skill, Research Planning Protocol and ⚠️ Verification Notice, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Neuropsych Battery Selector is an agent skill from NeuroAIHub/BrainPilot. Domain-validated decision logic for selecting neuropsychological test batteries matched to suspected cognitive deficit profiles

Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/deficit-profiles.md` and `references/test-catalog.md`).

The repository describes itself as: BrainPilot: Automating Brain Discovery with Agentic Research. The licence is AGPL-3.0.

Example prompts

  • “/neuropsych-battery-selector”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Clarify the Referral Question
  2. Identify Target Cognitive Domains
  3. Assemble the Battery
  4. Select Appropriate Norms
  5. Address Common Pitfalls
  6. Condition-Specific Battery Recommendations

What it can do on your machine

Read from SKILL.md and the folder at commit 93f6855. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Neuropsych Battery Selector loads about 4k tokens when it runs, and up to ~15k if it reads all its reference files. Until then it costs about 39 tokens; SKILL.md has 2,008 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~15k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from NeuroAIHub/BrainPilot at commit 93f6855, republished under its AGPL-3.0 licence (© NeuroAIHub). 2,008 words, ~4,022 tokens.

Download SKILL.mdSave it as .claude/skills/neuropsych-battery-selector/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
neuropsych-battery-selector
description
Domain-validated decision logic for selecting neuropsychological test batteries matched to suspected cognitive deficit profiles
domain
clinical-neuroscience
authors
Claude Code Agent
version
1.0.0
papers
Lezak et al., 2012, Strauss et al., 2006, Mitrushina et al., 2005, Heilbronner et al., 2010
dependencies.required
research-literacy
review_status
ai-generated

Neuropsychological Battery Selector

Purpose

Selecting a neuropsychological test battery is a clinical judgment task, not a checklist exercise. A competent programmer without clinical neuropsychology training will get this wrong because:

  • Not all "memory tests" test the same construct. The CVLT-II/III assesses list learning with encoding strategies; Logical Memory tests narrative recall; the BVMT-R tests visual-spatial memory. Each is sensitive to different lesion profiles (Lezak et al., 2012, Ch. 11).
  • Test selection must match the referral question. A dementia screen requires different instruments than a TBI return-to-work evaluation or a pre-surgical epilepsy workup.
  • Normative data are not interchangeable. Age, education, cultural background, and premorbid ability all determine which norms to apply and whether a given score is actually impaired (Mitrushina et al., 2005).
  • Redundant tests waste time and fatigue patients. Over-testing degrades performance and inflates apparent impairment, particularly in older adults and those with attentional deficits (Strauss et al., 2006).

When to Use This Skill

Use this skill when you need to:

  • Select neuropsychological tests matched to a suspected cognitive deficit profile
  • Assemble a battery for a specific referral question (dementia differential, TBI, pre-surgical, forensic)
  • Advise on which cognitive domains to assess given a neurological condition
  • Evaluate whether a proposed battery has adequate domain coverage or problematic redundancy
  • Choose between brief screening vs. comprehensive evaluation

Do NOT use this skill for:

  • Interpreting test scores (that requires a different skill)
  • Diagnosing neurological conditions from test results alone
  • Administering tests (this requires licensed clinical training)

Research Planning Protocol

Before executing the domain-specific steps below, you MUST:

  1. State the research question -- What cognitive domain(s) are being assessed and why?
  2. Justify the method choice -- Why neuropsychological testing (not neuroimaging, behavioral paradigm)? What alternatives were considered?
  3. Declare expected outcomes -- What deficit pattern would support the clinical/research hypothesis?
  4. Note assumptions and limitations -- What does this battery assume about the patient? Where could it mislead?
  5. Present the plan to the user and WAIT for confirmation before proceeding.

For detailed methodology guidance, see the research-literacy skill.


⚠️ Verification Notice

This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please open an issue.

Step 1: Clarify the Referral Question

The referral question determines everything. Map it to one of these categories:

Referral TypePrimary GoalTypical Battery Length
Dementia differential diagnosisDistinguish AD vs. FTD vs. VaD vs. DLB3--4 hours
Mild cognitive impairment screeningDetect early decline, track progression1.5--2 hours
TBI evaluation (acute/subacute)Document deficits, guide rehabilitation2--3 hours
TBI evaluation (chronic/forensic)Quantify residual deficits, effort testing4--6 hours
Pre-surgical epilepsy workupLateralize/localize function, predict risk3--5 hours
Psychiatric differentialDistinguish cognitive vs. psychiatric etiology2--3 hours
Return-to-work/fitness-for-dutyFunctional capacity in specific domains2--4 hours

(Lezak et al., 2012, Ch. 5; Sweet et al., 2011 -- 78% of neuropsychologists use a flexible battery approach)


Step 2: Identify Target Cognitive Domains

Based on the referral question and suspected condition, select domains to assess. Every battery MUST cover at least attention/processing speed, memory, and executive function. Add domains based on the clinical picture.

Cognitive Domain Framework

Attention / Processing Speed

  • WAIS-IV Processing Speed Index (Coding, Symbol Search): ~15 min (Wechsler, 2008)
  • Trail Making Test Part A: ~3 min (Reitan, 1958; deficient if >78 sec, ages 25--54)
  • Continuous Performance Test (CPT-3): ~14 min (Conners, 2014)
  • WAIS-IV Digit Span (Forward): ~5 min (Wechsler, 2008)

Executive Function

  • Wisconsin Card Sorting Test (WCST-64): ~15 min (Heaton et al., 1993)
  • Trail Making Test Part B: ~5 min (Reitan, 1958; deficient if >273 sec, ages 25--54)
  • Stroop Color-Word Test: ~5 min (Golden, 1978)
  • Tower of London/D-KEFS Tower: ~15 min (Shallice, 1982; Delis et al., 2001)
  • Verbal Fluency -- FAS: ~5 min (Benton et al., 1994; mean ~36--44 words total for ages 25--54, education 12+ years)
  • Verbal Fluency -- Animals: ~2 min (Strauss et al., 2006; mean ~20--24 animals for ages 25--54)

Memory

  • WMS-IV (Logical Memory I & II, Verbal Paired Associates I & II): ~30--45 min including delay (Wechsler, 2009)
  • CVLT-II/CVLT-3 (California Verbal Learning Test): ~30 min (Delis et al., 2000/2017)
  • RAVLT (Rey Auditory Verbal Learning Test): ~15 min (Rey, 1964; Schmidt, 1996)
  • BVMT-R (Brief Visuospatial Memory Test--Revised): ~25 min including delay (Benedict, 1997)
  • Logical Memory (WMS-IV): immediate and delayed recall; sensitivity 90--95% for MCI when combined with CVLT (Rabin et al., 2009)

Language

  • Boston Naming Test (BNT-60): ~15--20 min (Kaplan et al., 1983)
  • Token Test (short form): ~10 min (De Renzi & Vignolo, 1962)
  • Controlled Oral Word Association (COWA/FAS): ~5 min (listed above under executive; also indexes language)
  • Western Aphasia Battery--Revised (WAB-R): ~30--60 min (Kertesz, 2007; use for suspected aphasia)

Visuospatial / Visuoconstructional

  • Rey Complex Figure Test -- Copy: ~5--10 min (Osterrieth, 1944; Meyers & Meyers, 1995)
  • WAIS-IV Block Design: ~10 min (Wechsler, 2008)
  • Judgment of Line Orientation (JLO): ~15 min (Benton et al., 1994)
  • Hooper Visual Organization Test (VOT): ~15 min (Hooper, 1983)

Motor Function

  • Grooved Pegboard: ~5 min per hand (Klove, 1963; Ruff & Parker, 1993)
  • Finger Tapping Test: ~10 min (Halstead, 1947; Reitan & Wolfson, 1993)

Step 3: Assemble the Battery

Core Battery (~2--3 hours)

Every evaluation should include these unless contraindicated:

DomainRecommended Core Test(s)Time
Premorbid estimateTOPF or WTAR~10 min
Attention / Processing SpeedTMT-A + WAIS-IV Coding + Digit Span~20 min
Executive FunctionTMT-B + Verbal Fluency (FAS + Animals) + Stroop~15 min
Verbal MemoryCVLT-II/III or RAVLT~30 min
Visual MemoryBVMT-R or RCFT recall~25 min
LanguageBNT (30- or 60-item)~15 min
VisuospatialRCFT Copy or Block Design~10 min
MotorGrooved Pegboard (bilateral)~10 min
Effort/ValidityTOMM Trial 1 or embedded measures~10 min
Total~145 min
Extended Battery (~4--6 hours)

Add these for complex referrals (forensic, dementia differential, pre-surgical):

DomainAdditional TestsTime
Intelligence estimateWAIS-IV (4 index scores)~70 min
Memory (expanded)WMS-IV (full battery)~75 min
Executive (expanded)WCST-64 + Tower~30 min
Language (expanded)Token Test + WAB-R~40 min
Visuospatial (expanded)JLO + Hooper VOT~30 min
Effort/Validity (expanded)TOMM (full) + WMT or MSVT~30 min
Added time~275 min
Assembly Rules
  1. One verbal learning test: Choose CVLT-II/III OR RAVLT, not both. They measure overlapping constructs (Strauss et al., 2006--778).
  2. One copy figure: RCFT copy OR Block Design for visuoconstruction screening. Use both only if visuospatial function is the primary question.
  3. Delay intervals: Schedule verbal memory delay recall (~20--30 min after learning) during non-memory tasks. Same for visual memory delay.
  4. Fatigue management: Place demanding tests (WCST, CVLT) early. Place motor tests as breaks. Offer rest periods every 60--90 min (Lezak et al., 2012, Ch. 6).
  5. At least one validity measure: Mandatory. Use TOMM Trial 1 (sensitivity 83%, specificity 93% at cutoff <=40; Denning, 2012) as a minimum. For forensic cases, use two or more PVTs from different modalities (Sweet et al., 2011).

Step 4: Select Appropriate Norms

Normative Data Decision Tree
  1. Age: Always match. Most tests provide age-stratified norms.
  2. Education: Use education-corrected norms when available (e.g., Heaton et al., 2004 norms for TMT, WCST, verbal fluency).
  3. Premorbid IQ: For patients with estimated IQ far from average, IQ-adjusted norms improve accuracy over education alone. MOANS norms found BNT, Token Test, and JLO correlate more strongly with IQ (r = .47--.61) than with education (r = .24--.31) (Steinberg et al., 2005).
  4. Cultural/linguistic background: US-normed tests may overestimate impairment in non-English speakers or culturally diverse populations (Lucas et al., 2005; Pena-Casanova et al., 2009). Use population-specific norms when available (e.g., NP-NUMBRS for Spanish speakers).
  5. Sex: Match when norms are available. Grooved Pegboard shows significant sex differences: women faster than men (Ruff & Parker, 1993). Finger Tapping: men faster, especially in older groups.
Show full SKILL.md (759 more words)Show less
Premorbid Estimation
  • TOPF (Test of Premorbid Functioning): 70 irregular words, co-normed with WAIS-IV/WMS-IV, IQ range 53--141 (Pearson, 2009). Preferred for current use.
  • WTAR (Wechsler Test of Adult Reading): predecessor to TOPF, co-normed with WAIS-III/WMS-III (Wechsler, 2001). Acceptable if TOPF unavailable.
  • Caution: Both underestimate premorbid IQ in high-functioning individuals and overestimate in low-functioning individuals (Bright & van der Linde, 2020). Supplement with demographic-based estimates.

Step 5: Address Common Pitfalls

Practice Effects in Serial Assessment
  • Practice effects average d = 0.24--0.28 on composite scores at 6--12 month retest intervals (Calamia et al., 2012).
  • No consensus on minimum retest interval; effects persist for 2+ years on some measures (Heilbronner et al., 2010).
  • Tests most susceptible: PASAT, Stroop interference, verbal fluency, TMT-B (Beglinger et al., 2005).
  • Tests least susceptible: Digit Span, Letter-Number Sequencing (Beglinger et al., 2005).
  • Mitigation: Use alternate forms (CVLT-II has alternate form; RAVLT has multiple lists). Apply reliable change indices (RCIs) or standardized regression-based norms to interpret change (Chelune et al., 1993).
Ceiling and Floor Effects
  • Ceiling effects: TMT-A and simple attention tests may miss mild deficits in high-functioning individuals. Add more demanding measures (e.g., PASAT, D-KEFS verbal fluency switching) (Strauss et al., 2006).
  • Floor effects: WCST and complex tests may be too difficult for moderate-to-severe dementia. Substitute with simpler tasks (e.g., clock drawing, category fluency) (Lezak et al., 2012, Ch. 18).
Ecological Validity
  • Neuropsychological tests have modest correlations (r = .3--.5) with real-world functioning (Chaytor & Schmitter-Edgecombe, 2003).
  • Supplement with functional measures (e.g., Independent Living Scales, IADL checklists) when the referral question concerns everyday competence.
  • Executive function tests have particularly limited ecological validity; consider adding the Behavioral Assessment of the Dysexecutive Syndrome (BADS) or real-world task simulations (Wilson et al., 1996).
Symptom Validity Testing
  • TOMM standard cutoff (<45 Trial 2): specificity .96--1.00 but sensitivity only .15--.50 (Tombaugh, 1996). Use Trial 1 cutoff <=40 for better sensitivity (.83) at .93 specificity (Denning, 2012).
  • WMT (Word Memory Test): more sensitive than TOMM but higher false-positive rate in genuine MCI/dementia -- 67% of MCI patients classified as "poor effort" at standard cutoffs (Green, 2003). Use hard-easy comparison scores instead (sensitivity/specificity ~95%).
  • Embedded PVTs: Reliable Digit Span (RDS >= 7 as cutoff; Greiffenstein et al., 1994), CVLT-II Forced Choice <=15 (Delis et al., 2000). Use multiple embedded measures to supplement standalone PVTs.
  • Rule: In forensic and disability evaluations, include at least two standalone PVTs and two embedded PVTs (Larrabee, 2012).

Step 6: Condition-Specific Battery Recommendations

For expected deficit profiles by condition, see references/deficit-profiles.md. Below are summary battery modifications:

ConditionAdd to CoreRemove/De-emphasizeKey Rationale
Alzheimer's (suspected)WMS-IV full, CVLT-3 intrusion analysis, BNT-60May shorten executive batteryMemory encoding/storage is primary deficit (Weintraub et al., 2012)
FTD (behavioral variant)WCST, D-KEFS, social cognition measures, personality inventoryDe-emphasize visuospatialExecutive/behavioral profile dominates (Rascovsky et al., 2011)
Vascular dementiaProcessing speed emphasis (Coding, Symbol Search), TMT-A/B, verbal fluencyMay abbreviate languageProcessing speed and executive function most affected (Sachdev et al., 2014)
TBI (moderate-severe)CPT-3, PASAT, verbal fluency, motor tests bilateralNone -- broad battery neededDiffuse deficits: attention, speed, memory, executive (Rabinowitz & Levin, 2014)
Temporal lobe epilepsyVerbal/visual memory (laterality-specific), BNT, verbal fluencyMay abbreviate motorMemory lateralization critical for surgical planning (Jones-Gotman et al., 2010)
Parkinson's diseaseVerbal fluency (semantic + phonemic), JLO, clock drawing, Grooved PegboardNoneDual-syndrome: frontostriatal vs. posterior cortical (Kehagia et al., 2013)
Multiple sclerosisSDMT, PASAT, CVLT-II/III, BVMT-RMay abbreviate languageBICAMS recommended minimum battery (Langdon et al., 2012): SDMT + CVLT-II + BVMT-R

Quick Reference: Test-to-Domain Mapping

For a comprehensive catalog of tests with administration times, normative samples, and sensitivity data, see references/test-catalog.md.


Key References

  • Benton, A. L., Sivan, A. B., Hamsher, K., Varney, N. R., & Spreen, O. (1994). Contributions to Neuropsychological Assessment (2nd ed.). Oxford University Press.
  • Delis, D. C., Kaplan, E., & Kramer, J. H. (2001). Delis-Kaplan Executive Function System. Pearson.
  • Heaton, R. K., Miller, S. W., Taylor, M. J., & Grant, I. (2004). Revised Comprehensive Norms for an Expanded Halstead-Reitan Battery. PAR.
  • Heilbronner, R. L., Sweet, J. J., Attix, D. K., Krull, K. R., Henry, G. K., & Hart, R. P. (2010). Official position of the AACN on serial neuropsychological assessments. The Clinical Neuropsychologist, 24, 1267--1278.
  • Lezak, M. D., Howieson, D. B., Bigler, E. D., & Tranel, D. (2012). Neuropsychological Assessment (5th ed.). Oxford University Press.
  • Mitrushina, M., Boone, K. B., Razani, J., & D'Elia, L. F. (2005). Handbook of Normative Data for Neuropsychological Assessment (2nd ed.). Oxford University Press.
  • Strauss, E., Sherman, E. M. S., & Spreen, O. (2006). A Compendium of Neuropsychological Tests (3rd ed.). Oxford University Press.
  • Sweet, J. J., Nelson, N. W., & Moberg, P. J. (2011). The TCN/AACN 2010 "salary survey." The Clinical Neuropsychologist, 25, 218--245.

© NeuroAIHub, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in packages/skills/skills/10_Clinical_Neuropsychology/neuropsych-battery-selector of NeuroAIHub/BrainPilot.

  • SKILL.md
  • references/deficit-profiles.md
  • references/test-catalog.md

Open the folder on GitHubat commit 93f6855

Compare with similar skills

Neuropsych Battery Selector next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Neuropsych Battery Selector compared with similar skills
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Domain Selectionkostja94/marketing-skills1k—~1.3kAutomated safety check: PassMIT
Ddd Validateruvnet/ruflo74k—~643Automated safety check: NotesMIT
Form Validationthedaviddias/Front-End-Checklist74k—~633Automated safety check: PassMIT
Has Selectorthedaviddias/Front-End-Checklist74k—~547Automated safety check: PassMIT

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Questions about Neuropsych Battery Selector

What does Neuropsych Battery Selector do?

Domain-validated decision logic for selecting neuropsychological test batteries matched to suspected cognitive deficit profiles. Neuropsych Battery Selector is an agent skill from NeuroAIHub/BrainPilot.

How do I install Neuropsych Battery Selector in Claude Code?

Run `npx skills add NeuroAIHub/BrainPilot --skill neuropsych-battery-selector -a claude-code`. Or copy the skill folder (packages/skills/skills/10_Clinical_Neuropsychology/neuropsych-battery-selector in NeuroAIHub/BrainPilot) into .claude/skills/neuropsych-battery-selector in your project. Claude Code loads it when a task matches its description.

How do I install Neuropsych Battery Selector in Codex?

Run `npx skills add NeuroAIHub/BrainPilot --skill neuropsych-battery-selector -a codex`. Or copy the skill folder (packages/skills/skills/10_Clinical_Neuropsychology/neuropsych-battery-selector in NeuroAIHub/BrainPilot) into .agents/skills/neuropsych-battery-selector in your project. Codex loads it when a task matches its description.

Can I use Neuropsych Battery Selector in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NeuroAIHub/BrainPilot --skill neuropsych-battery-selector -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/neuropsych-battery-selector, .gemini/skills/neuropsych-battery-selector, .github/skills/neuropsych-battery-selector and .opencode/skills/neuropsych-battery-selector in your project.

What does Neuropsych Battery Selector need to run?

SKILL.md names no scripts, command-line tools or credentials: Neuropsych Battery Selector is instructions for the agent only.

Does Neuropsych Battery Selector access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Neuropsych Battery Selector safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Neuropsych Battery Selector use?

Neuropsych Battery Selector is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Neuropsych Battery Selector use?

About 4k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.

What are the alternatives to Neuropsych Battery Selector?

Skills that share tags, products or a category with Neuropsych Battery Selector: Validate Selector (simstudioai/sim, 30k stars), Domain Selection (kostja94/marketing-skills, 1k stars), Ddd Validate (ruvnet/ruflo, 74k stars) and Form Validation (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Neuropsych Battery Selector?

NeuroAIHub (a GitHub organization) maintains it in NeuroAIHub/BrainPilot, which has 1,062 GitHub stars. The repository holds 59 skills in this directory. The repository was last updated on October 2, 2026.

Source: NeuroAIHub/BrainPilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.