aigd-iterate

aigd-iterate is a skill for Claude Code, Codex from ProdaZhang/aigd. It costs 87 tokens per session (775 once invoked), scanned A, original, MIT.

A playtesting iteration guide for AIGD prototypes. AIGD is a staged process for designing and refining interactive systems or games.

In plain words
What is it for?
Use it after testing a prototype to update its rules, configuration table, and prototype file, and to record the system's playtesting status.
Why use it?
It keeps feedback-driven changes focused on the rules, test data, and prototype while the design is still changing.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads .claude/ paths; mentions Claude Code.

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.

agentmods
npx agentmods add skills/prodazhang/aigd/aigd-iterate
Any agent
npx skills add ProdaZhang/aigd --skill aigd-iterate
Clone the repo
git clone --depth 1 https://github.com/ProdaZhang/aigd

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 aigd-iterate

README.md
[![agentmods](https://agentmods.dev/badge/skills/prodazhang/aigd/aigd-iterate.svg)](https://agentmods.dev/skills/prodazhang/aigd/aigd-iterate)
Your own site
<a href="https://agentmods.dev/skills/prodazhang/aigd/aigd-iterate"><img src="https://agentmods.dev/badge/skills/prodazhang/aigd/aigd-iterate.svg" alt="Measured on agentmods" height="20"></a>
Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 775 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00087 $0.00775
Opus 5 $0.00044 $0.00387
Sonnet 5 $0.00017 $0.00155
Haiku 4.5 $0.00009 $0.00077

Measured 6d ago against content hash e69910061a1b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

aigd-iterate 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 6d 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.

aigd-iterate/SKILL.md · 40 lines

How it starts

The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AIGD · iterate (playtest iteration) [minimal skeleton]

Package contract: install the whole aigd package (the orchestrator aigd/+references/ and the 6 sub-skills (including aigd-ui-capture) placed at the same level in this environment's skills directory, following the host agent, e.g. Claude Code's .claude/skills/), don't copy this skill alone — this package's sub-skills rely on aigd/ at the same level to fetch the methodology, copying it alone breaks the link.

Positioning

Phase 3. Loops between system (2) ↔ iterate (3), repeatable. The design is still fluid, so only change rules / config (test data) / prototype — the proto/acceptance haven't even been produced yet, and zero churn is exactly the essence of how this step saves cost.

Read / produce / write back

  • Read: this system in the manifest, the user's playtest feedback.
  • Produce / change: rules.md / config table (test data) / system prototype.html.
  • Write back: this system's status in the manifestPlaytesting (currently playtesting; a system bounced back from handoff also stays Playtesting, don't overwrite it back to Draft); record this round's iteration points (what changed, why).

Recipe

  1. Collect playtest feedback → locate whether it's a rule problem or a value problem.
  2. Change the corresponding artifact (rules → change -01, numbers → change config test data, presentation → change prototype).
  3. Re-emit the prototype → playtest again → loop, until the user is satisfied → move to aigd-handoff to finalize.

Playtest-feedback format (filled by the user or the AI after playtesting, fed to this skill — the locating decides which artifact to change)

Dimension Problem description Locating (rule/value/presentation/other) Repro steps
<e.g. combat pacing> <too long a wait after casting a skill> <value> <enter combat → tap skill → watch cooldown>

Read the full file on GitHub · 40 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. 6d ago First seen · 40 lines · 87 tokens per session scan A e69910061a1b

Subscribe to this mod's changes

aigd-iterate is a skill published in the GitHub repository ProdaZhang/aigd (2 stars, last pushed 2mo ago), licensed MIT. It adds 87 tokens to every session and 775 once invoked, about $0.0004 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 2026-08-31.

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