Borrowing it
Nothing to install: this file belongs to rajbos/ai-engineering-fluency. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/rajbos/ai-engineering-fluency/main/.claude/skills/create-issue/SKILL.mdgit clone --depth 1 https://github.com/rajbos/ai-engineering-fluencyWrote 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.
[](https://agentmods.dev/skills/rajbos/ai-engineering-fluency/create-issue)<a href="https://agentmods.dev/skills/rajbos/ai-engineering-fluency/create-issue"><img src="https://agentmods.dev/badge/skills/rajbos/ai-engineering-fluency/create-issue/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.
<a href="https://agentmods.dev/skills/rajbos/ai-engineering-fluency/create-issue"><img src="https://agentmods.dev/badge/skills/rajbos/ai-engineering-fluency/create-issue.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00106 | $0.01898 |
| Opus 5.5 | $0.00042 | $0.00759 |
| Sonnet 5.5 | $0.00021 | $0.00380 |
| Haiku 4.5 | $0.00011 | $0.00190 |
Grade A, and why
create-issue 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 yesterday.
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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Issue Skill
This skill is guidance only (no scripts). It describes how issues in this repo must be prepared before they are filed, so that whoever picks the issue up (a person or a coding agent) can start without re-doing the research.
When to Use This Skill
Use it whenever you are asked to create, file or write up an issue for this repository — features, bugs, improvements, tech debt. Do not file an issue from a one-line request without going through the steps below.
Step 1 — Understand what and where
Get the following from the user. Take what they already said; do not re-ask for it.
- What should be implemented, fixed or changed, and why (the problem or the value).
- Where it shows up: which surface(s) — VS Code extension, CLI, Visual Studio, JetBrains, desktop app, sharing-server, copilot-app canvas, docs/scripts — and which view/tab/command if it is UI.
- For bugs: steps to reproduce, expected vs. actual, versions/editor involved.
If any of this is unclear, ambiguous or you detect a gap (e.g. the request names a view but not what data it should show, or it is unclear whether other surfaces should get it too), ask the user before continuing. Ask concise, specific questions; batch them in one message. Prefer a recommendation ("I assume X, correct?") over open-ended questions. If the user cannot answer, record the open question in the issue instead of guessing.
Step 2 — Investigate the codebase
Before writing anything, look at the code. Do not describe changes from memory.
- Start from
AGENTS.md(repo structure, sub-project instructions) and the matching.github/instructions/*.instructions.md. - If
.graphify-agent/graph.jsonexists, query it for structural questions (callers, blast radius), e.g.GRAPHIFY_OUT=.graphify-agent graphify query "<question>"(or pass--graph .graphify-agent/graph.json). Ignore any localgraphify-out/directory (stale, not the CI graph); if the graph is missing, search with grep/glob. - Check
docs/(especiallydocs/features/,docs/adr/,docs/FLUENCY-METRICS-SCHEMA.md,docs/TRACKABLE-DATA.md) for existing design decisions that apply. - Search existing open and recently closed issues/PRs (
gh issue list --state all --search "<keywords>",gh pr list --state all --search "<keywords>") to avoid duplicates; link related ones instead of duplicating.
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.
- yesterday First seen · 111 lines · 106 tokens per session scan A 33b85723102e
create-issue is a skill published in the GitHub repository rajbos/ai-engineering-fluency (119 stars, last pushed yesterday), licensed MIT. It adds 106 tokens to every session and 1,898 once invoked, about $0.0004 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 2026-10-26.
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