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Issue Create

Community
fagemx
issue-create

Create GitHub issues for gstack-game improvements — skill gaps, wrong benchmarks, new skill proposals, template bugs. Maps conversation context into actionable issues with proper labels and skill references.

Overview

Publisherfagemx
Repositorygstack-game
Skill nameissue-create
Stars
81
Forks
10
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by fagemx on GitHub. Read the source before you install it.

Installation

Install the Issue Create AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/fagemx/gstack-game/tree/main/.claude/skills/issue-create
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/fagemx/gstack-game.git /tmp/gstack-game
mkdir -p .claude/skills
cp -r /tmp/gstack-game/.claude/skills/issue-create .claude/skills/issue-create
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Issue Create in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Issue Create on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Issue Create is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Preamble (run first)

bash
_GD_VERSION="0.3.0"
# Find gstack-game bin directory (installed in project or standalone)
_GG_BIN=""
for _p in ".claude/skills/gstack-game/bin" ".claude/skills/game-review/../../gstack-game/bin" "$(dirname "$(readlink -f .claude/skills/game-review/SKILL.md 2>/dev/null)" 2>/dev/null)/../../bin"; do
  [ -f "$_p/gstack-config" ] && _GG_BIN="$_p" && break
done
[ -z "$_GG_BIN" ] && echo "WARN: gstack-game bin/ not found, some features disabled"

# Project identification
_SLUG=$(basename "$(git rev-parse --show-toplevel 2>/dev/null || pwd)")
_BRANCH=$(git branch --show-current 2>/dev/null || echo "unknown")
_USER=$(whoami 2>/dev/null || echo "unknown")

# Session tracking
mkdir -p ~/.gstack/sessions
touch ~/.gstack/sessions/"$PPID"
_PROACTIVE=$([ -n "$_GG_BIN" ] && "$_GG_BIN/gstack-config" get proactive 2>/dev/null || echo "true")
_TEL_START=$(date +%s)
_SESSION_ID="$-$(date +%s)"

# Shared artifact storage (cross-skill, cross-session)
mkdir -p ~/.gstack/projects/$_SLUG
_PROJECTS_DIR=~/.gstack/projects/$_SLUG

# Telemetry
mkdir -p ~/.gstack/analytics
echo '{"skill":"issue-create","ts":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'","repo":"'"$_SLUG"'","branch":"'"$_BRANCH"'"}'  >> ~/.gstack/analytics/skill-usage.jsonl 2>/dev/null || true

echo "SLUG: $_SLUG"
echo "BRANCH: $_BRANCH"
echo "PROACTIVE: $_PROACTIVE"
echo "PROJECTS_DIR: $_PROJECTS_DIR"
echo "GD_VERSION: $_GD_VERSION"

Shared artifact directory: $_PROJECTS_DIR (~/.gstack/projects/{slug}/) stores all skill outputs:

  • Design docs from /game-ideation
  • Review reports from /game-review, /balance-review, etc.
  • Player journey maps from /player-experience

All skills read from this directory on startup to find prior work. All skills write their output here for downstream consumption.

If PROACTIVE is "false", do not proactively suggest gstack-game skills.

AskUserQuestion Format (Game Design)

ALWAYS follow this structure for every AskUserQuestion call:

  1. Re-ground: Project, branch, what game/feature is being reviewed. (1-2 sentences)
  2. Simplify: Plain language a smart 16-year-old gamer could follow. Use game examples they'd know (Minecraft, Genshin, Among Us, etc.) as analogies.
  3. Recommend: RECOMMENDATION: Choose [X] because [one-line reason] — include Player Impact: X/10 for each option. Calibration: 10 = fundamentally changes player experience, 7 = noticeable improvement, 3 = cosmetic/marginal.
  4. Options: Lettered: A) ... B) ... C) ... with effort estimates (human: ~X / CC: ~Y).

Game-specific vocabulary — USE these terms, don't reinvent:

  • Core loop, session loop, meta loop
  • FTUE (First Time User Experience), aha moment, churn point
  • Retention hook (D1, D7, D30)
  • Economy: sink, faucet, currency, exchange rate
  • Progression: skill gate, content gate, time gate
  • Bartle types: Achiever, Explorer, Socializer, Killer
  • Difficulty curve, flow state, friction point
  • Whale, dolphin, minnow (spending tiers)

Completion Status Protocol

DONE / DONE_WITH_CONCERNS / BLOCKED / NEEDS_CONTEXT. Escalation after 3 failed attempts.

Telemetry (run last)

bash
_TEL_END=$(date +%s)
_TEL_DUR=$(( _TEL_END - _TEL_START ))
[ -n "$_GG_BIN" ] && "$_GG_BIN/gstack-telemetry-log" \
  --skill "issue-create" --duration "$_TEL_DUR" --outcome "OUTCOME" \
  --used-browse "false" --session-id "$_SESSION_ID" 2>/dev/null &

/issue-create: Create gstack-game Issue

Create well-structured GitHub issues for improving gstack-game skills from conversation context.

Arguments

Parse $ARGUMENTS to determine operation:

  • skill-gap — A skill is missing domain knowledge, has wrong numbers, or gives bad advice
  • new-skill — Propose a new skill that doesn't exist yet
  • bug — Template bug, build issue, or broken skill behavior
  • (empty or create) — General issue; auto-detect type from conversation

Operation: skill-gap

Report that a skill needs domain expert input — wrong benchmark, missing gotcha, bad scoring weight, or absent forcing question.

This is the most common issue type for gstack-game. Maps directly to the contribution templates in .github/ISSUE_TEMPLATE/.

Step 1: Identify the Gap

From conversation context, extract:

  • Which skill? (/game-review, /balance-review, etc.)
  • Which file? (a references/*.md file, or the .tmpl itself)
  • Gap type: benchmark / gotcha / forcing-question / scoring / persona / missing-section
  • What's wrong or missing? Specific content
  • Evidence: Why this is wrong (experience, data source, playtest observation)

If running a gstack-game review skill revealed the gap (e.g., /balance-review gave bad advice on idle games), capture:

  • The specific bad advice or missing check
  • What the correct behavior should be
  • The game type or context where it fails

Step 2: Clarify with User

STOP. AskUserQuestion to confirm:

  1. Is the skill identification correct?
  2. Is this a wrong value (fix existing) or missing content (add new)?
  3. What's the evidence source? (shipped game experience, published data, playtest results, industry standard)
  4. Severity: Does this cause wrong scores (critical) or missing depth (important)?

Step 3: Select Issue Template

Map gap type to GitHub Issue template:

Gap typeTemplateLabel
Wrong benchmark numberbenchmark.ymlskill-gap, benchmark
Claude gives wrong advicegotcha.ymlskill-gap, gotcha
Missing review questionforcing-question.ymlskill-gap, forcing-question
Scoring weight wrongscoring.ymlskill-gap, scoring
Missing section/content(general)skill-gap, content

Step 4: Create Issue

bash
gh issue create \
  --title "skill-gap(<SKILL_NAME>): <concise description>" \
  --body "<formatted content>" \
  --label "skill-gap,<gap-type>"

Body structure:

markdown
## Skill
`/<skill-name>` — `skills/<skill-name>/references/<file>.md`

## Current Behavior
<What the skill currently says or does>

## Expected Behavior
<What it should say or do instead>

## Evidence
<Source: shipped game experience, published data, playtest, industry standard>
<Contributor expertise if stated: "[Role, N years, shipped N titles]">

## Game Type Context
<When does this matter? All games? Only F2P mobile? Only multiplayer?>

---
_Created from conversation via `/issue-create skill-gap`_

Step 5: Return Result

Display the issue URL. Example:

Issue created: https://github.com/owner/repo/issues/123
Skill: /balance-review | Type: gotcha | File: references/gotchas.md

Operation: new-skill

Propose a new skill that fills a gap in the gstack-game workflow.

Step 1: Identify the Gap

From conversation context, determine:

  • What workflow stage is missing? (Design / Bridge / Validation / Release / Meta)
  • What does this skill do that no existing skill covers?
  • Who is the target user? (designer, programmer, QA, producer, artist)
  • What upstream skills feed into it? What downstream skills consume its output?

Step 2: Check for Overlap

Before creating the issue, verify no existing skill already covers this:

bash
ls skills/*/SKILL.md.tmpl | head -30

Cross-reference against the 28 existing skills. If overlap exists, this might be a skill-gap issue instead (expanding an existing skill).

STOP. AskUserQuestion:

  1. Confirm no overlap with existing skills
  2. Which workflow layer does this belong to? (A: Design, B: Bridge, C: Validation, D: Meta)
  3. What quality tier is realistic? (B-type 70%+ needs domain expert; A-type 55%+ is achievable without)
  4. Is the proposer willing to contribute domain knowledge, or just identifying the gap?

Step 3: Create Issue

bash
gh issue create \
  --title "feat: new skill /<skill-name> — <one-line purpose>" \
  --body "<formatted content>" \
  --label "new-skill,enhancement"

Body structure:

markdown
## Proposed Skill
`/<skill-name>` — <one-line description>

## Workflow Position
- **Layer:** Design / Bridge / Validation / Meta
- **Upstream:** Which skills feed into this? (e.g., `/game-review` output)
- **Downstream:** Which skills consume this output?

## What It Does
<2-3 paragraphs describing the skill's purpose, who uses it, when>

## Why It's Needed
<What gap does this fill? What goes wrong without it?>

## Suggested Sections
1. <Section name> — <what it checks>
2. <Section name> — <what it checks>
...

## Domain Expertise Needed
<What kind of expert could calibrate this skill?>

## Reference Skills
<Which existing gstack-game skills are most similar in structure?>

---
_Created from conversation via `/issue-create new-skill`_

Operation: bug

Report a template bug, build issue, or broken skill behavior.

Step 1: Gather Bug Information

From conversation context, extract:

  • What broke? (build failure, wrong output, template error, drift, test failure)
  • Which file? (.tmpl, generated .md, scripts/, bin/, test/)
  • Repro steps (exact commands that fail)
  • Error output (paste exact error, not paraphrased)

Step 2: Clarify with User

STOP. AskUserQuestion:

  1. Can you reproduce this consistently?
  2. Which platform? (Windows/Git Bash, macOS, Linux, WSL)
  3. Did bun test pass before this happened?

Step 3: Create Issue

bash
gh issue create \
  --title "bug: <concise description>" \
  --body "<formatted content>" \
  --label "bug"

Body structure:

markdown
## Bug Description
<What's broken>

## Steps to Reproduce
1. ...
2. ...
3. ...

## Expected Behavior
<What should happen>

## Actual Behavior
<What happens instead>

## Environment
- Platform: <Windows/macOS/Linux>
- Shell: <bash/zsh/Git Bash/WSL>
- Bun version: <output of `bun --version`>
- gstack-game version: <content of VERSION file>

## Error Output

Created from conversation via /issue-create bug


---

## Operation: create (default)

General issue from conversation context. Auto-detect type.

### Step 1: Analyze Conversation

Review conversation to identify:
- Is this about a specific skill's content? → Likely `skill-gap`
- Is this about a missing workflow step? → Likely `new-skill`
- Is this about something broken? → Likely `bug`
- Something else? → General issue

### Step 2: Route or Create

If a specific operation matches, follow that operation's workflow.

Otherwise, create a general issue:

```bash
gh issue create \
  --title "<type>: <description>" \
  --body "<synthesized content>" \
  --label "<appropriate labels>"

Title prefixes:

  • feat: — enhancement to existing skill
  • docs: — documentation improvement
  • refactor: — template restructuring
  • chore: — build, CI, tooling
  • perf: — build performance or skill execution improvement

AUTO/ASK/ESCALATE

  • AUTO: Label selection, template matching, formatting
  • ASK: Issue type confirmation, scope verification, skill identification
  • ESCALATE: Contradicts existing domain knowledge, affects scoring accuracy, touches multiple skills

Anti-Sycophancy

Forbidden:

  • ❌ "Great catch!"
  • ❌ "This is a really important issue"
  • ❌ "Excellent observation"

Instead: State the gap factually. "The idle game economy model in /balance-review flags inflation >1.2 as a problem. Idle games use inflation as a core mechanic — this is a false positive for that genre."

Review Log

bash
[ -n "$_GG_BIN" ] && "$_GG_BIN/gstack-review-log" '{"skill":"issue-create","timestamp":"TIMESTAMP","status":"STATUS","operation":"OPERATION","target_skill":"TARGET","commit":"COMMIT"}' 2>/dev/null || true

Frequently asked questions

What does the Issue Create AI skill do?

Create GitHub issues for gstack-game improvements — skill gaps, wrong benchmarks, new skill proposals, template bugs. Maps conversation context into actionable issues with proper labels and skill references.

Why use Issue Create on TypingMind?

Because you install it once and use it with any model. Issue Create is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Issue Create in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/fagemx/gstack-game/tree/main/.claude/skills/issue-create. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Issue Create?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Issue Create?

As many as you like. As long as a model supports skills, you can use Issue Create with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Issue Create AI skill free?

Yes. It is published on GitHub by fagemx under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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