
Tla Plus Expert
- 40 installs
- 70 repo stars
- Updated July 26, 2026
- rysweet/amplihack
Helps with ai & agent building tasks.
About
tla-plus-expert is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.
- tla-plus-expert
- AI & Agent Building
- AI-coding skill
Tla Plus Expert by the numbers
- 40 all-time installs (skills.sh)
- +1 installs in the week ending Jul 26, 2026 (Skillselion tracking)
- Ranked #8,167 of 16,556 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 2, 2026 (Skillselion catalog sync)
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| Installs | 40 |
|---|---|
| repo stars | ★ 70 |
| Last updated | July 26, 2026 |
| Repository | rysweet/amplihack ↗ |
What it does
Helps with ai & agent building tasks.
Files
TLA+ Expert Skill
Purpose
Provides expert-level TLA+ formal specification assistance for designing, verifying, and reasoning about concurrent and distributed systems within amplihack.
When This Skill Activates
- User asks to write or review a TLA+ specification
- User needs help with model checking (TLC) configuration or output interpretation
- User wants to formally verify a protocol or workflow design
- User asks about invariants, liveness properties, or safety properties
- User wants to apply formal methods to amplihack components
- User mentions PlusCal or wants to translate between PlusCal and TLA+
- User references Lamport, Demirbas, or formal methods best practices
How It Works
This skill delegates to the tla-plus-expert agent which has deep knowledge of:
1. TLA+ language and idioms — writing specs, operators, temporal formulas 2. TLC model checker — configuration, trace interpretation, state space management 3. Seven mental models (Demirbas) — abstraction, global shared memory, local guards, invariants, stepwise refinement, atomicity refinement, communication 4. Industry case studies — 8 production uses from AWS, MongoDB, Microsoft Azure 5. AI + TLA+ limitations — SysMoBench findings on LLM capabilities and guardrails 6. amplihack experiment infrastructure — manifest-driven experiments, heuristic scoring, TLC validation integration
Integration with Existing Infrastructure
The amplihack repo includes a TLA+ experiment runner at crates/amplihack-eval/src/tla_prompt_experiment.rs with:
- Manifest-driven experiment matrix (models x prompt variants x repeats)
- 6 heuristic scoring dimensions
- Real TLC validation support
- Replay and live execution modes
TLA+ specs live in experiments/hive_mind/tla_prompt_language/specs/.
Usage Examples
# Write a spec for a new protocol
/tla-plus-expert Write a TLA+ spec for our consensus voting workflow
# Review an existing spec
/tla-plus-expert Review specs/SmartOrchestrator.tla for correctness
# Help with TLC output
/tla-plus-expert TLC found a counterexample in my spec, help me understand it
# Decide if TLA+ is appropriate
/tla-plus-expert Should I formally specify this retry cascade logic?
# Generate invariants
/tla-plus-expert What invariants should I check for a parallel workstream manager?Key Resources
- TLA+ specs:
experiments/hive_mind/tla_prompt_language/specs/ - Experiment runner:
crates/amplihack-eval/src/tla_prompt_experiment.rs - TLC binary:
/usr/local/bin/tlc(if installed) - Issue #3939: TLA+ integration roadmap