Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ArabelaTso/Skills-4-SE --skill tlaplus-spec-generatorgit clone --depth 1 https://github.com/ArabelaTso/Skills-4-SEWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/arabelatso/skills-4-se/tlaplus-spec-generator)<a href="https://agentmods.dev/skills/arabelatso/skills-4-se/tlaplus-spec-generator"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/tlaplus-spec-generator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/arabelatso/skills-4-se/tlaplus-spec-generator"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/tlaplus-spec-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00118 | $0.02176 |
| Opus 5 | $0.00059 | $0.01088 |
| Sonnet 5 | $0.00024 | $0.00435 |
| Haiku 4.5 | $0.00012 | $0.00218 |
Grade A, and why
tlaplus-spec-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 308 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TLA+ Spec Generator
Automatically generate TLA+ specifications from program implementations for formal verification of distributed systems.
Overview
This skill transforms imperative programs (C/C++, Python) into declarative TLA+ specifications. It analyzes program structure to identify state variables, actions, and system behavior, then generates well-structured TLA+ modules suitable for model checking with TLC.
Workflow
1. Analyze Source Code
Generate TLA+ specification from source files:
# Single file
python3 scripts/generate_spec.py program.py -o Spec.tla
# Multiple files
python3 scripts/generate_spec.py server.py client.py protocol.py -o Protocol.tla
# With module name
python3 scripts/generate_spec.py distributed_system.c -o System.tla --module-name DistributedSystem
The generator automatically:
- Detects programming language
- Parses source code
- Identifies state variables and actions
- Extracts system structure
- Generates TLA+ specification
2. Specify System Parameters
For distributed systems, specify the number of processes:
python3 scripts/generate_spec.py consensus.py -o Consensus.tla --processes 3
This creates a constant N in the TLA+ spec representing the number of processes/nodes.
3. Generated Output
The generator produces two files:
1. Spec.tla - Complete TLA+ specification:
---- MODULE Spec ----
EXTENDS Naturals, Sequences, FiniteSets, TLC
CONSTANTS N \* Number of processes
VARIABLES
state,
messages,
committed
vars == <<state, messages, committed>>
TypeOK ==
/\ state \in [1..N -> {"Init", "Working", "Done"}]
/\ messages \in SUBSET Messages
/\ committed \in SUBSET Operations
Init ==
/\ state = [p \in 1..N |-> "Init"]
/\ messages = {}
/\ committed = {}
SendMessage(p, msg) ==
/\ state[p] = "Working"
/\ messages' = messages \cup {msg}
/\ UNCHANGED <<state, committed>>
Next ==
\/ \E p \in 1..N, msg \in Messages : SendMessage(p, msg)
Spec == Init /\ [][Next]_vars
====
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 308 lines · 118 tokens per session scan A b87054317091
tlaplus-spec-generator is a skill published in the GitHub repository ArabelaTso/Skills-4-SE (252 stars, last pushed 22d ago), licensed Apache-2.0. It adds 118 tokens to every session and 2,176 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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