fizzbee: Skill for Claude Code

.claude/skills/fizz-spec/SKILL.md

fizz-spec is a skill for Claude Code from fizzbee-io/fizzbee. It costs 53 tokens per session (3,472 once invoked), scanned A, original, Apache-2.0.

A guide for writing FizzBee files, which describe distributed systems in a Python-like language so a model checker can examine their behavior. It covers system state, actions, roles, assertions, and verification settings.

In plain words
What is it for?
Creating, editing, or reviewing .fizz specifications, including invariants, liveness properties, fault settings, and model-checking options.
Why use it?
It helps developers express expected system behavior and find safety or liveness problems before relying on production tests.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: reads .claude/ paths.

This is fizzbee-io/fizzbee's own configuration. It tells Claude Code how to work on fizzbee itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything fizzbee configures →

Reuse

Borrowing it

Nothing to install: this file belongs to fizzbee-io/fizzbee. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/fizzbee-io/fizzbee/main/.claude/skills/fizz-spec/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/fizzbee-io/fizzbee

Made for: Claude Code.

Wrote 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.

agentmods badge for fizz-spec

README.md
[![agentmods](https://agentmods.dev/badge/skills/fizzbee-io/fizzbee/fizz-spec/github.svg)](https://agentmods.dev/skills/fizzbee-io/fizzbee/fizz-spec)
Your own site
<a href="https://agentmods.dev/skills/fizzbee-io/fizzbee/fizz-spec"><img src="https://agentmods.dev/badge/skills/fizzbee-io/fizzbee/fizz-spec/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.

agentmods 80×15 button for fizz-spec

Your own site · 80×15
<a href="https://agentmods.dev/skills/fizzbee-io/fizzbee/fizz-spec"><img src="https://agentmods.dev/badge/skills/fizzbee-io/fizzbee/fizz-spec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,472 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Rogue Agent · line 4
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
  • medium Rogue Agent · line 379
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00053 $0.03472
Opus 5.5 $0.00021 $0.01389
Sonnet 5.5 $0.00011 $0.00694
Haiku 4.5 $0.00005 $0.00347

Measured 2mo ago against content hash 1038ef38ce04, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

fizz-spec 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 2mo 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.

.claude/skills/fizz-spec/SKILL.md · 450 lines

How it starts

The opening of the file, as written. The whole thing — 450 lines — stays where its author put it; the contents beside it link to each section on GitHub.

FizzBee Spec Writing

FizzBee is a Python-like formal spec language built on Starlark. Specs model distributed systems; the model checker exhaustively verifies safety and liveness properties.

Full reference: ~/.claude/skills/fizzbee-docs/LANGUAGE_REFERENCE.md Examples index: ~/.claude/skills/fizzbee-docs/README.md

Installation

brew tap fizzbee-io/fizzbee && brew install fizzbee
# Then run: fizz spec.fizz

File Structure

---
# Optional YAML frontmatter
options:
  max_actions: 100
  max_concurrent_actions: 2   # 1 for single-user apps
  crash_on_yield: true        # enable fault injection

action_options:
  "RoleName.ActionName":
    max_actions: 10

deadlock_detection: true      # false for interactive apps
liveness: strict
---

Then the Fizz spec:

  1. Top-level constants
  2. Functions (pure helpers)
  3. Roles (actors/processes)
  4. Top-level actions (Init + others)
  5. Assertions

Core Syntax

Constants and Global State

MAX = 10                        # constant
State = enum('IDLE', 'RUNNING') # enum

action Init:
    counter = 0      # becomes global state variable
    items = []
    server = Server()  # create role instance

Actions

# Modifier order: [flow] [fairness] action Name
atomic action Increment:        # atomic = no interleaving
    counter = counter + 1

fair action Progress:           # fair = weak fairness
    require not done
    done = True

atomic fair action Produce:     # both modifiers
    require len(queue) < MAX
    queue.append(item)

Key rules:

  • No parameters on actions
  • Init runs once; all variables defined in it become global state
  • require condition disables the action (doesn't execute it)
  • An action is "enabled" only after it executes a simple statement (=, method call, pass)

Roles

@state(ephemeral=['cache'])     # cache resets on crash
role Server:
    action Init:
        self.data = {}          # role state (persists)
        self.cache = {}         # ephemeral (resets on crash)

    atomic func Read(key):      # function: can have params + return
        return self.data.get(key, None)

    action Write:
        key = oneof self.pending_keys
        self.data[key] = self.pending[key]

Read the full file on GitHub · 450 lines

Changes

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.

  1. 2mo ago First seen · 450 lines · 53 tokens per session scan A 1038ef38ce04

Subscribe to this mod's changes

fizz-spec is a skill published in the GitHub repository fizzbee-io/fizzbee (366 stars, last pushed yesterday), licensed Apache-2.0. It adds 53 tokens to every session and 3,472 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.

Related

Other skills, from other repositories

tla-check

Write and iteratively refine executable TLA+ specs (.tla) and TLC model configs (.cfg) from natural-language system designs; run TLC model checking; summarize pass/fail and counterexamples with explicit assumptions and bounds. Use when asked to design or validate a protocol/state machine, create or edit .tla/.cfg…

younes-io/agent-skills · 79 tokens

tla-proof

Write and iteratively refine TLA+ theorem proofs in .tla modules with TLAPS (tlapm); run proof checks and summarize proved vs failed/omitted obligations with explicit assumptions and trust boundaries. Use when asked to create or fix THEOREM or PROOF blocks, diagnose TLAPS failures, strengthen inductive invariants…

younes-io/agent-skills · 87 tokens

epistemic-uncertainty-quantification

Extend Sounio's epistemic types with advanced uncertainty quantification methods, such as confidence intervals, non‑Gaussian distributions, and Dempster‑Shafer evidence combination, positioning the language at the state‑of‑the‑art in measurement science.

Sounio-lang/sounio · 62 tokens

sounio-epistemic-types

Work on Sounio epistemic computing: Knowledge/uncertainty/confidence/provenance, ontology bindings, and dependent epistemic subtyping/proofs; use when editing stdlib/epistemic/.

Sounio-lang/sounio · 54 tokens

sounio-l0-core

L0 epistemic core of Sounio: language identity, epistemic invariants, and effect discipline; use when explaining or extending the L0 language semantics.

Sounio-lang/sounio · 40 tokens

sounio-ontology

Work on Sounio scientific ontology integration (term resolution, embeddings, semantic typing, federated ontologies); use when editing stdlib/ontology/ or ontology-related diagnostics/types.

Sounio-lang/sounio · 43 tokens