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 agentmods add skills/fradser/dotclaude/create-issuesnpx skills add FradSer/dotclaude --skill create-issuesgit clone --depth 1 https://github.com/FradSer/dotclaudeWhat 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 | $0.00054 | $0.00805 |
| Opus 5 | $0.00027 | $0.00402 |
| Sonnet 5 | $0.00011 | $0.00161 |
| Haiku 4.5 | $0.00005 | $0.00081 |
Grade A, and why
create-issues 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 2d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create GitHub Issues
Execute automated GitHub issue creation workflow for $ARGUMENTS following TDD principles and conventional commit standards.
Context
- Current git status: !
git status - Current branch: !
git branch --show-current - Open issues: !
gh issue list --state open --limit 10 - GitHub authentication: !
gh auth status
Requirements Summary
Follow TDD principles, conventional commits, and protected branch workflows. Use proper labels, auto-closing keywords, and atomic commits. See references/requirements.md for complete standards.
Phase 1: Repository Analysis
Goal: Assess repository state, detect templates, and determine issue scope and type.
Actions:
- Analyze current branch from context (main/develop vs PR branch)
- Review open issues to identify duplicates or related work
- Check for contributing guidelines (
CONTRIBUTING.md) and follow its requirements - Detect issue templates in
.github/ISSUE_TEMPLATE/directory - If templates exist: select appropriate template using
gh issue create --list - Determine issue type (epic, PR-scoped, or review) based on
$ARGUMENTScomplexity - Apply branch-based decision logic from
references/decision-logic.md
See references/repository-templates.md for template detection and compliance details.
Phase 2: Issue Creation
Goal: Create GitHub issue with proper structure, labels, and links.
Actions:
- Create or verify required priority labels exist (see
references/decision-logic.mdfor commands) - Draft issue following structure requirements in
references/issue-structure.md - Apply appropriate labels (priority, type) using
--label- Assign owners using
--assignee - Link milestones using
--milestoneor projects using--projectif requested
- Assign owners using
- Add auto-closing keywords if PR-scoped issue (NOT for epics)
- CRITICAL: auto-closing keywords only fire when the PR merges into the repository's default branch. If the issue will be resolved by a PR targeting a non-default branch, warn the user that the issue will NOT close automatically and must be closed manually — see
references/auto-closing-keywords.mdfor the full rule and keyword table.
- CRITICAL: auto-closing keywords only fire when the PR merges into the repository's default branch. If the issue will be resolved by a PR targeting a non-default branch, warn the user that the issue will NOT close automatically and must be closed manually — see
- Link to related issues or epics if applicable
What ships with it
7 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.
- 2d ago First seen · 71 lines · 54 tokens per session scan A dca004720d2d
create-issues is a skill published in the GitHub repository FradSer/dotclaude (588 stars, last pushed 21d ago), licensed MIT. It adds 54 tokens to every session and 805 once invoked, about $0.0003 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.