Provide implementations of advanced data structures
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
FreePublished on GitHub
behavior-contract
Bug condition/postcondition formalization as testable Behavior Contracts. Defines invariants that must be preserved across fixes.
The English summary is being prepared. Showing the original description.
See how to installFiles included (2)
- SKILL.md2.2 KB
- README.md620 B
SKILL.md (original)
Review the instructions the agent will receive before you install.
- "Positive amounts still process correctly"
- "Negative amounts still throw
InvalidAmountError" - "Receipt format remains unchanged for all amount types"
Contract Document Template
# Behavior Contract: [Bug Title]
## Bug Condition
[Precise description of triggering conditions]
## Postcondition
[Expected correct behavior after fix]
## Invariants
- [ ] Invariant 1: [existing behavior to preserve]
- [ ] Invariant 2: [existing behavior to preserve]
## Testable Assertions
1. `expect(processPayment(0)).toEqual({ amount: 0, status: 'completed' })`
2. `expect(processPayment(100)).toEqual({ amount: 100, status: 'completed' })`
3. `expect(() => processPayment(-1)).toThrow(InvalidAmountError)`
Usage in Bugfix Workflow
- Bug analysis identifies root cause at file:line
- This skill formalizes the contract from the analysis
- tdd-enforcer writes failing test from Bug Condition
- tdd-enforcer writes preservation tests from Invariants
- Minimal fix applied, contract audited
Reviews
No reviews yet. Tell others what you thought.
Comments
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
More skills from this repository
Fresh adversarial code review with binary PASS/FAIL verdicts, evidence citations, and anchoring bias prevention via fresh reviewer spawning.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
agent-booster
FreeWASM-based instant code transforms for simple tasks, achieving 352x speedup over LLM inference with zero cost.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
Coordinate Crew (persistent) and Polecat (transient) agents using Gas Town's hook-based work distribution and GUPP principle.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
Generate visual representations of algorithm execution
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
anti-drift
FreeHierarchical coordination and drift detection with frequent checkpoints, shared memory coherence validation, role specialization enforcement, and short task cycles.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026