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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)
npx skills add https://github.com/rysweet/amplihack --skill tla-plus-expert

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Listed on Skillselion
Installs40
repo stars70
Last updatedJuly 26, 2026
Repositoryrysweet/amplihack

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

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

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