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/nimble-giant/nimble-mold/create-issuenpx skills add nimble-giant/nimble-mold --skill create-issuegit clone --depth 1 https://github.com/nimble-giant/nimble-moldWrote 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/nimble-giant/nimble-mold/create-issue)<a href="https://agentmods.dev/skills/nimble-giant/nimble-mold/create-issue"><img src="https://agentmods.dev/badge/skills/nimble-giant/nimble-mold/create-issue.svg" alt="Measured on agentmods" 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 | $0.00048 | $0.00884 |
| Opus 5 | $0.00024 | $0.00442 |
| Sonnet 5 | $0.00010 | $0.00177 |
| Haiku 4.5 | $0.00005 | $0.00088 |
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 5d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Github Issue
Purpose
This command generates {{scm.provider}} issues with a clean, actionable, well-structured format. It is optimized for creating consistent {{scm.provider}} issues for engineering planning, with consistent formatting across feat, fix, chore, docs, and epic types.
Command Name
create-issue
Invocation Syntax
You can invoke this command with optional flags:
/create-github-issue [flags] <description>
Flags
-b, --board <name>: Specify project board (default: "{{project.board}}")-l, --label <label>: Add labels to the issue (can be used multiple times)--prompt: Enable interactive mode (prompts for board and labels if supported)--local: Save the issue as a local markdown file in theplans/directory instead of creating a {{scm.provider}} issue
Examples
# Basic issue creation (no board or labels)
/create-github-issue feat(web): add control family status card
# With project board
/create-github-issue --board "Tech Debt" fix(api): memory leak in cache
# With labels
/create-github-issue -l bug -l priority:high fix(security): patch vulnerability
# Multiple labels and board
/create-github-issue -b "Backend" -l enhancement -l good-first-issue feat(api): add new endpoint
# Interactive mode for teams with complex configurations
/create-github-issue --prompt feat(web): new feature requiring custom setup
# Save locally as a markdown file in plans/ (private, no GitHub issue created)
/create-github-issue --local feat(web): new feature to plan privately
{{- if .agent.plan_mode.enabled }}
- Immediately {{agent.plan_mode.enter}} when this command is invoked
- Parse the user input to extract flags and issue description
- Format the {{scm.provider}} issue using the exact markdown structure below
- Use {{agent.plan_mode.exit}} to present the formatted issue as the plan
- Wait for user approval before proceeding
- After approval:
- If
--promptflag is present: Use interactive mode (ask for board and labels if repository supports them) - Otherwise: Use parsed flags only (no prompting, no automatic assignments)
- If
- Execute the {{scm.provider}} CLI commands to create the issue with configured settings {{- else }}
- Parse the user input to extract flags and issue description
- Format the {{scm.provider}} issue using the exact markdown structure below
- Present the formatted issue for user review
- Wait for user approval before proceeding
- After approval:
- If
--promptflag is present: Use interactive mode (ask for board and labels if repository supports them) - Otherwise: Use parsed flags only (no prompting, no automatic assignments)
- If
- Execute the {{scm.provider}} CLI commands to create the issue with configured settings {{- end }}
What ships with it
3 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.
- 5d ago First seen · 100 lines · 48 tokens per session scan A af8cc77475d2
create-issue is a skill published in the GitHub repository nimble-giant/nimble-mold (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 48 tokens to every session and 884 once invoked, about $0.0002 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
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…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…