Hypothesis Generation
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
Expert guidance for selecting and parameterizing cognitive psychology experimental paradigms based on research questions
$ npx skills add NeuroAIHub/BrainPilot --skill cognitive-paradigm-design -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NeuroAIHub/BrainPilot cognitive-paradigm-design --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NeuroAIHub/BrainPilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design .claude/skills/cognitive-paradigm-design && rm -rf skills-srcUse ~/.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/
Install the "cognitive-paradigm-design" agent skill from https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design into .claude/skills/cognitive-paradigm-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognitive-paradigm-design", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-designType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NeuroAIHub/BrainPilot --skill cognitive-paradigm-design -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NeuroAIHub/BrainPilot cognitive-paradigm-design --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NeuroAIHub/BrainPilot.git skills-src && mkdir -p .agents/skills && cp -r skills-src/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design .agents/skills/cognitive-paradigm-design && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cognitive-paradigm-design" agent skill from https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design into .agents/skills/cognitive-paradigm-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognitive-paradigm-design", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NeuroAIHub/BrainPilot --skill cognitive-paradigm-design -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NeuroAIHub/BrainPilot cognitive-paradigm-design --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NeuroAIHub/BrainPilot.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design .cursor/skills/cognitive-paradigm-design && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "cognitive-paradigm-design" agent skill from https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design into .cursor/skills/cognitive-paradigm-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognitive-paradigm-design", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NeuroAIHub/BrainPilot.git --path packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NeuroAIHub/BrainPilot --skill cognitive-paradigm-design -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NeuroAIHub/BrainPilot cognitive-paradigm-design --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NeuroAIHub/BrainPilot.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design .gemini/skills/cognitive-paradigm-design && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "cognitive-paradigm-design" agent skill from https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design into .gemini/skills/cognitive-paradigm-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognitive-paradigm-design", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NeuroAIHub/BrainPilot cognitive-paradigm-designInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NeuroAIHub/BrainPilot --skill cognitive-paradigm-design -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NeuroAIHub/BrainPilot.git skills-src && mkdir -p .github/skills && cp -r skills-src/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design .github/skills/cognitive-paradigm-design && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "cognitive-paradigm-design" agent skill from https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design into .github/skills/cognitive-paradigm-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognitive-paradigm-design", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NeuroAIHub/BrainPilot --skill cognitive-paradigm-design -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NeuroAIHub/BrainPilot cognitive-paradigm-design --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NeuroAIHub/BrainPilot.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design .opencode/skills/cognitive-paradigm-design && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "cognitive-paradigm-design" agent skill from https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design into .opencode/skills/cognitive-paradigm-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognitive-paradigm-design", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
cognitive-paradigm-designExpert guidance for selecting and parameterizing cognitive psychology experimental paradigms based on research questions
Cognitive Paradigm Design is an agent skill from NeuroAIHub/BrainPilot. Expert guidance for selecting and parameterizing cognitive psychology experimental paradigms based on research questions
Its SKILL.md is about 3.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/classic-paradigms.md` and `references/design-principles.md`).
It sits in Research & Science, covering Hypothesis generation. The repository describes itself as: BrainPilot: Automating Brain Discovery with Agentic Research. The licence is AGPL-3.0.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 93f6855. It shows what the files ask for, not the result of running them.
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.
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.
Links to these hosts (documentation or services it may open):
github.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Cognitive Paradigm Design loads about 3.9k tokens when it runs, and up to ~17k if it reads all its reference files. Until then it costs about 37 tokens; SKILL.md has 1,831 words of instructions outside code blocks.
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.
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.
The full file from NeuroAIHub/BrainPilot at commit 93f6855, republished under its AGPL-3.0 licence (© NeuroAIHub). 1,831 words, ~3,937 tokens.
.claude/skills/cognitive-paradigm-design/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.This skill helps researchers select appropriate experimental paradigms for cognitive psychology research questions, configure their parameters with cited defaults, and design proper controls. It encodes methodological knowledge from the cognitive experimental literature that a non-specialist would not know.
For detailed paradigm parameters, see references/classic-paradigms.md.
For design methodology, see references/design-principles.md.
Before executing the domain-specific steps below, you MUST:
For detailed methodology guidance, see the research-literacy skill.
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.
When given a research question, follow this sequence:
Map the research question to one or more core cognitive domains:
| Domain | Core Constructs | Example Research Questions |
|---|---|---|
| Attention | Selective attention, spatial orienting, temporal attention, attentional capture | "Does emotion capture attention automatically?" |
| Memory | Encoding, retrieval, WM capacity, false memory, recognition vs. recall | "Do older adults show increased false memory?" |
| Decision Making | Risk, reward learning, impulsivity, perceptual decisions | "Are substance users more impulsive in intertemporal choice?" |
| Perception | Thresholds, masking, awareness, object recognition | "What is the contrast threshold for face detection?" |
| Language | Lexical access, sentence parsing, semantic processing | "Does syntactic complexity slow reading at the verb?" |
| Executive Function | Inhibition, task switching, updating, cognitive flexibility | "Is SSRT longer in ADHD children?" |
Use this decision tree to narrow paradigm choices:
Attention:
Memory:
Decision Making:
Perception:
Language:
Executive Function:
For each selected paradigm, consult references/classic-paradigms.md for the full parameter reference. Apply these general rules:
| Parameter | Default | Adjustment Rule |
|---|---|---|
| Stimulus duration | Until response (RT tasks) or 100-500 ms (brief presentation) | Shorten for masking or iconic memory studies; lengthen for patient populations |
| ISI / ITI | 1000-2000 ms | Increase to 2000-3000 ms for EEG (to separate ERPs); increase for fMRI (jittered 2-8 s for HRF deconvolution) |
| SOA | Paradigm-specific (see reference) | Short SOA (<300 ms): automatic processes; Long SOA (>500 ms): strategic/controlled processes (Neely, 1977) |
| Response deadline | 1500-2000 ms for RT tasks | Tighten for speed-emphasis; loosen for accuracy-emphasis or elderly/clinical samples |
| Scenario | Minimum Trials per Condition | Rationale |
|---|---|---|
| Large effect (d > 0.8) | 40-60 | Stroop, Flanker, AB (Hedge et al., 2018) |
| Medium effect (d ~ 0.5) | 60-100 | Priming, switching, search slopes (McNamara, 2005; Monsell, 2003) |
| Small effect (d ~ 0.3) | 100-200 | Subtle manipulations, individual differences (Baker et al., 2021) |
| SDT measures (d', c) | 100+ total (50+ signal, 50+ noise) | Macmillan & Creelman (2005) |
| Reliability-critical (SSRT, K) | 160-200 total | Verbruggen et al. (2019); Rouder et al. (2011) |
Apply these control procedures:
references/design-principles.md, Section 1 for the full decision frameworkreferences/design-principles.md, Section 5.4)| Paradigm Type | Primary DV | Analysis Notes |
|---|---|---|
| Speeded RT tasks | RT (ms) + accuracy (%) | Always report both. Apply RT trimming: remove anticipatory (<200 ms) and slow (>2.5 SD or >2000 ms) responses. Analyze only correct trials for RT. |
| Accuracy-focused tasks | Proportion correct or d' | Use SDT when signal/noise distinction applies (Macmillan & Creelman, 2005) |
| Memory tasks | Hit rate, false alarm rate, d', K | Cowan's K for change detection; d' for recognition |
| Adaptive threshold | Threshold estimate | Average last 6-8 reversals (staircase); maximum-likelihood estimate (QUEST) |
| Learning/decision tasks | Block-by-block performance | IGT: (C+D)-(A+B) per block of 20; Delay discounting: indifference points per delay |
| Research Question Type | First-Choice Paradigm | Alternative |
|---|---|---|
| Does X capture attention? | Posner cueing / Visual search | Dot-probe task |
| Does X interfere with processing? | Stroop / Flanker | Simon task |
| What is VWM capacity for X? | Change detection | Continuous report |
| Does X cause false memories? | DRM paradigm | Misinformation paradigm |
| Is recognition based on recollection or familiarity? | Remember-Know | ROC analysis |
| Does X affect inhibitory control? | Stop-signal (SSRT) | Go/No-Go |
| Does X modulate cognitive flexibility? | Task switching | Wisconsin Card Sorting |
| Is X processed without awareness? | Backward masking + priming | Continuous flash suppression |
| What is the perceptual threshold for X? | QUEST / Staircase + 2AFC | Method of constant stimuli |
| Does X affect reading? | Self-paced reading / Eye-tracking | ERP (N400, P600) |
| Does X prime Y? | Semantic priming + LDT | Cross-modal priming |
| Is X related to impulsivity? | Delay discounting | Stop-signal |
| Does X affect decision making under risk? | Iowa Gambling Task | Balloon Analogue Risk Task |
| Does X affect WM updating? | N-back | Operation span |
These are non-obvious pitfalls that require domain expertise:
Stroop: Using fewer than 4 color-response mappings introduces item-specific contingency learning that mimics Stroop effects but is not conflict-based (Schmidt & Besner, 2008). Always use >= 4 colors.
Stop-signal: Never estimate SSRT from mean Go RT alone. The integration method accounts for the Go RT distribution shape. Failed-stop RTs must be faster than Go RTs (independence assumption check; Logan & Cowan, 1984). Use the consensus guide (Verbruggen et al., 2019).
Attentional blink: T1 must be masked (by a trailing distractor). Removing the T1+1 item eliminates the AB entirely (Raymond et al., 1992). Always include T1+1 distractor.
Change detection (VWM): Retention intervals shorter than ~900 ms may allow iconic memory to contribute, inflating K estimates. Use >=900 ms retention interval, and consider articulatory suppression to prevent verbal recoding (Luck & Vogel, 1997; Vogel et al., 2001).
DRM: False recall varies dramatically across lists (10-60%). Always report which word lists were used and their BAS values (Stadler et al., 1999). Roediger et al. (2001) normed 55 lists.
Iowa Gambling Task: Apparent "learning" may reflect frequency-of-loss avoidance rather than long-term value sensitivity. Consider deck-by-deck analysis, not just (C+D)-(A+B) (Steingroever et al., 2013).
Priming: High relatedness proportions (>50%) inflate priming through strategic expectancy, not automatic spreading activation. Use RP <= 25% to isolate automatic priming (Neely et al., 1989).
Task switching: In alternating-runs designs (AABB), the response-stimulus interval (RSI) is confounded with cue-stimulus interval (CSI). Use cued-switching designs to separate preparation time from passive decay (Monsell, 2003; Meiran, 1996).
Psychophysical staircases: Step sizes of <5% lead to staircases that fail to generate enough reversals. Use initial step sizes of at least 10-20% of the expected threshold range, then halve after the first 2-4 reversals (Garcia-Perez, 1998).
N-back: Omission errors are more informative than commission errors (unlike Go/No-Go). Always report d' rather than raw accuracy, as d' separates sensitivity from bias (Haatveit et al., 2010). Include lure trials (n-1 or n+1 matches) to assess interference susceptibility (Gray et al., 2003).
© 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
SKILL.md and 2 other files (references) in packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design of NeuroAIHub/BrainPilot.
Open the folder on GitHubat commit 93f6855
Cognitive Paradigm Design 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Cognitive Paradigm Design this skillNeuroAIHub/BrainPilot | 1.1k | — | ~3.9k | Automated safety check: Pass | AGPL-3.0 | |
| Hypothesis Generationspacering-net/codeg | 3.9k | 14 repos | ~3.6k | Automated safety check: Notes | MIT | |
| Nature Paper CardYuan1z0825/nature-skills | 47k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Hypothesis GenerationK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.9k | Automated safety check: Pass | MIT | |
| Good QuestionRimagination/good-question | 305 | 1 repos | ~4.3k | Automated safety check: Pass | MIT | |
| High Stakes Analytics Decision Lablimingrui679-design/high-stakes-analytics-decision-lab | 1k | — | ~2.2k | Automated safety check: Pass | MIT |
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Categories
Expert guidance for selecting and parameterizing cognitive psychology experimental paradigms based on research questions. Cognitive Paradigm Design is an agent skill from NeuroAIHub/BrainPilot.
Cognitive Paradigm Design fits situations like: tasks that involve Hypothesis generation.
Run `npx skills add NeuroAIHub/BrainPilot --skill cognitive-paradigm-design -a claude-code`. Or copy the skill folder (packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design in NeuroAIHub/BrainPilot) into .claude/skills/cognitive-paradigm-design in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NeuroAIHub/BrainPilot --skill cognitive-paradigm-design -a codex`. Or copy the skill folder (packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design in NeuroAIHub/BrainPilot) into .agents/skills/cognitive-paradigm-design in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NeuroAIHub/BrainPilot --skill cognitive-paradigm-design -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cognitive-paradigm-design, .gemini/skills/cognitive-paradigm-design, .github/skills/cognitive-paradigm-design and .opencode/skills/cognitive-paradigm-design in your project.
SKILL.md names no scripts, command-line tools or credentials: Cognitive Paradigm Design is instructions for the agent only.
SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.
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.
Cognitive Paradigm Design 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.
About 3.9k 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 13k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Cognitive Paradigm Design: Hypothesis Generation (spacering-net/codeg, 3.9k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars), Hypothesis Generation (K-Dense-AI/claude-scientific-writer, 2.4k stars) and Good Question (Rimagination/good-question, 305 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
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.