hypothesis-testing
Property-based testing with Hypothesis for discovering edge cases and validating invariants.
Skill by foryourhealth111-pixel
Chalk Labs
Need help deploying hypothesis-testing?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/foryourhealth111-pixel-hypothesis-testing
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: testing
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/hypothesis-testing
What's inside
- Skill name
hypothesis-testing- Description
- Property-based testing with Hypothesis for discovering edge cases and validating invariants. Use when implementing comprehensive test coverage, testing complex logic with many inputs, or validating mathematical properties and invariants across input domains. Triggered by: hypothesis, property-based testing, @given, strategies, generative testing.
- License
- Apache-2.0
- Instructions
- 862 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- body: 862 lines (spec recommends under 500)
Files (1)
- SKILL.md
SKILL.md (first lines)
# Hypothesis Property-Based Testing
Hypothesis is a powerful property-based testing library that automatically generates test cases to find edge cases and validate properties of your code.
## Core Concept
**Traditional example-based testing:**
```python
def test_addition():
assert add(2, 3) == 5
assert add(0, 0) == 0
assert add(-1, 1) == 0
```
**Property-based testing with Hypothesis:**
```python
from hypothesis import given
import hypothesis.strategies as st
@given(st.integers(), st.integers())
def test_addition_commutative(a, b):
"""Addition is commutative for ALL integers."""
assert add(a, b) == add(b, a)
```
Hypothesis generates hundreds of test cases automatically, including edge cases you might not think of.
## Installation
```bash
# Install hypothesis with pytest integration
uv add --dev hypothesis pytest
# Optional plugins
uv add --dev hypothesis[numpy] # NumPy strategies
uv add --dev hypothesis[pandas] # Pandas strategies
uv add --dev hypothesis[django] # Django model strategies
```
## Configuration
### pyproject.toml Configuration
```toml
[tool.pytest.ini_options]
# Hypothesis settings
addopts = [
"--hypothesis-show-statistics", # Show test statistics
"--hypothesis-seed=0", # Reproducible tests (optional)
]
[tool.hypothesis]
# Maximum number of examples to generate
max_examples = 200 # Default: 100, CI: 200+
# Deadline for each test case (milliseconds)
deadline = 1000 # Default: 200ms, None to disable
# Verbosity level (quiet, normal, verbose, debug)
verbosity = "normal"
# Fail fast on first error
derandomize = false # Set to true for deterministic tests
# Database for example storage
database = ".hypothesis/examples" # Store found failures
# Profile-specific settings
[tool.hypothesis.profiles.dev]
max_examples = 50
deadline = 1000
verbosity = "normal"
[tool.hypothesis.profiles.ci]
max_examples = 500
deadline = 5000
verbosity = "verbose"
[tool.hypothesis.profiles.debug]
max_examples = 10
deadline = null
verbosity = "debug"
```
### Activate Profile
```python
# tests/conftest.py
from hypothesis import settings, Verbosity
# Set default profile based on environment
import os
if os.getenv("CI"):
settings.load_profile("ci")
else:
settings.load_profile("dev")
# Or configure programmatically
settings.register_profile("custom", max_examples=100, deadline=500)
settings.load_profile("custom")
```
## Basic Usage
### Simple Property Tests
```python
from hypothesis import given, example
import hypothesis.strategies as st
# Test numeric properties
@given(st.integers())
def test_absolute_value_non_negative(x):
"""abs(x) is always non-negative."""
assert abs(x) >= 0
@given(st.integers(), st.integers())
def test_addition_associative(a, b, c):
"""Addition is associative: (a + b) + c == a + (b + c)."""From foryourhealth111-pixel/Vibe-Skills, Apache-2.0.
More from foryourhealth111-pixel/Vibe-Skills
- 0.843score
prowler-docs
prowler-cloud
Prowler documentation style guide and writing standards.
SkillAFreshness: A★ 3.8KClaude Code - 0.744score
speckit-specify
github-spec-kit
Create or update feature specifications from natural language descriptions.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.741score
speckit-tasks
github-spec-kit
Break down implementation plans into actionable task lists.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.741score
speckit-plan
github-spec-kit
Generate technical implementation plans from feature specifications.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.741score
speckit-taskstoissues
github-spec-kit
Convert tasks from tasks.md into GitHub issues.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.741score
speckit-analyze
github-spec-kit
Perform cross-artifact consistency analysis across spec.md, plan.md, and tasks.md.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.741score
speckit-clarify
github-spec-kit
Structured clarification workflow for underspecified requirements.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.741score
speckit-checklist
github-spec-kit
Generate custom quality checklists for validating requirements completeness and clarity.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.741score
speckit-constitution
github-spec-kit
Create or update project governing principles and development guidelines.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.741score
speckit-implement
github-spec-kit
Execute all tasks from the task breakdown to build the feature.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.652score
astropy
foryourhealth111-pixel
Comprehensive Python library for astronomy and astrophysics.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.652score
doc
foryourhealth111-pixel
Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus…
SkillAFreshness: A★ 3.8KClaude Code +9
Signals
- Stars
- 3,764
- Forks
- 341
- Open issues
- 36
- Last commit (this folder)
- Feb 26, 2026 (8 months ago)
- Last release
- Oct 18, 2026 (12 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from foryourhealth111-pixel
- 0.652score
bio-database-evidence
foryourhealth111-pixel
Unified biological database evidence owner.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.652score
biopython
foryourhealth111-pixel
Primary retained Python toolkit for molecular biology sequence work.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.652score
generating-test-reports
foryourhealth111-pixel
Generate structured test reports with pass/fail rollups, coverage summaries, and test artifacts.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.652score
alpha-vantage
foryourhealth111-pixel
Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the…
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.652score
astropy
foryourhealth111-pixel
Comprehensive Python library for astronomy and astrophysics.
SkillAFreshness: A★ 3.8KClaude Code +9 - 0.652score
datacommons-client
foryourhealth111-pixel
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources.
SkillAFreshness: A★ 3.8KClaude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get hypothesis-testing running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
hypothesis-testing skill. Agent Mart. https://agentmart.dev/skills/foryourhealth111-pixel-hypothesis-testing (last updated 2026-10-24)