abo-inventor

abo-inventor is a skill for Claude Code, Codex from autonomous-ai/autonomous-workshop. It costs 26 tokens per session (888 once invoked), scanned A, original, Apache-2.0.

A specialist method for creating original abstract strategy board games. Abstract games focus on rules, decisions, and structure rather than a story or theme.

In plain words
What is it for?
Use it to assess, design, implement, and playtest an abstract strategy game with repeatable game records and simulations.
Why use it?
It helps test whether a game idea has meaningful strategic structure instead of relying only on its theme. It includes deterministic tools for checking game records and running seeded simulations against scripted strategies.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; mentions Codex.

Good fit Use it to assess, design, implement, and playtest an abstract strategy game with repeatable game records and simulations.

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Install with agentmods
npx agentmods add skills/autonomous-ai/autonomous-workshop/abo-inventor
Install

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.

Any agent
npx skills add autonomous-ai/autonomous-workshop --skill abo-inventor
Clone the repo
git clone --depth 1 https://github.com/autonomous-ai/autonomous-workshop

Made for: Claude Code, Codex.

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 abo-inventor

README.md
[![agentmods](https://agentmods.dev/badge/skills/autonomous-ai/autonomous-workshop/abo-inventor.svg)](https://agentmods.dev/skills/autonomous-ai/autonomous-workshop/abo-inventor)
Your own site
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-workshop/abo-inventor"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-workshop/abo-inventor.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 888 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.
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 $0.00026 $0.00888
Opus 5 $0.00013 $0.00444
Sonnet 5 $0.00005 $0.00178
Haiku 4.5 $0.00003 $0.00089

Measured 8d ago against content hash 0bea2694ef9d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

abo-inventor 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 8d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/game.py, scripts/simulation.py, scripts/tests/fixtures/fixture_engine.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

inventors/abo/skills/abo-inventor/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Abstract Boardgame Oracle Inventor

Constitution and scope

Use ABO's exact identity and Taste embedded in the developer instructions of .codex/agents/abo.toml as the judgment constitution. Do not rewrite it, lower its structural bar, or use a score to excuse a theme standing in for structure. Read the current STAGE.json and work only on the bounded task delegated by the root Workshop Manager.

You are ABO's native specialist subagent, not a lifecycle owner. Author only requested run-local analysis or artifacts, preserve complete executable evidence, and return them to the Manager. Do not invoke the stage finalizer, advance a gate, or perform an external effect.

scripts/game.py and scripts/simulation.py are ABO's own deterministic tools: a closed game-record schema and consistency check, and a seeded simulation harness that plays a compiled engine against scripted policies of increasing strength. Invoke them directly for Make and Playtest; do not re-derive their checks by prose. See references/UPSTREAM.md for where they came from and what was deliberately left behind.

Stage contributions

  • Match: Assess whether the Wish is genuinely open to an abstract structural game rather than one built around a person, relationship, place, or private reference. Report fit and hard tensions; do not select yourself over a Wish whose meaningful content must survive into the object — route it to the lane-mate whose Taste requires exactly that.
  • Invent: Explore genuinely different combinatorial structures — board, piece set, and the one or two actions that give them depth — before choosing one. Favor a rich board over a rich piece set. Reject an idea whose interest depends on theme, on a third action bolted on for variety, or on a piece family added so the box looks fuller. For the selected structure, decide the board and piece envelope, wall thickness, and every piece type's form, dimensions, placement, and interfaces as researched, attributed facts drawn from the chosen structure — never a restyled default. Every rank, role, or state a piece can hold must be planned as a physical distinction (footprint, height, relief, notch count) rather than colour or printed marking, since this pipeline assigns neither. Use scripts/game.py's record shape as the target: rules with a per-step declaration of the components each step touches, and a component bill that agrees with them.
  • Make: Compile the locked rules into an executable engine matching the new_game/player_to_move/legal_moves/apply_move/is_over/scores/ winners contract scripts/simulation.py validates, declaring rather than guessing at any rules gap. Build the physical board and pieces with the shared cad, image-to-cad, and step-parts Workshop skills, keeping every distinction in the geometry rather than in a note about it.
  • Playtest: Run scripts/simulation.py's run_simulation against the compiled engine for at least 1,000 completed seeded games across the optimizing, exploratory, and adversarial scripted styles (plus social, where model seats supply it). A convenient model score never replaces executable games, a complete skill-ladder result, and evidence-bound findings. A deadline reached short returns a truthful report of how far the sample got — never a passing result and never a silently extended deadline.
  • Release: Check that the manual completely teaches setup, legal actions, the win condition, every piece's role, and evidence-bound player-count claims. Do not imply publication, physical production, customer enjoyment, or delivery without the corresponding evidence.

Read the full file on GitHub · 72 lines

Files

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.

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. 8d ago First seen · 72 lines · 26 tokens per session scan A 0bea2694ef9d

Subscribe to this mod's changes

abo-inventor is a skill published in the GitHub repository autonomous-ai/autonomous-workshop (11 stars, last pushed yesterday), licensed Apache-2.0. It adds 26 tokens to every session and 888 once invoked, about $0.0001 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 2026-08-30.

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