Agent skill

Create Issue With Websearch

by dyoshikawa in dyoshikawa/rulesync

Create a GitHub issue from a vague idea by thoroughly researching the topic on the web to sharpen the specification before filing

MITAuto-check passedDevelopment

Install Create Issue With Websearch

skills CLI
$ npx skills add dyoshikawa/rulesync --skill create-issue-with-websearch -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install dyoshikawa/rulesync create-issue-with-websearch --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/dyoshikawa/rulesync.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.rulesync/skills/create-issue-with-websearch .claude/skills/create-issue-with-websearch && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
create-issue-with-websearch
GitHub stars
1.5k
Token cost
~1.8k tokens
SKILL.md length
874 words
Files
1
Skills in repo
40
Repo updated
First seen
Licence
MIT

At a glance

Create a GitHub issue from a vague idea by thoroughly researching the topic on the web to sharpen the specification before filing

  • Works in 8 steps: Gather the Initial Idea → Research the Topic on the Web → Research the Codebase → …
  • Development work in your project
  • SKILL.md covers Step 1: Gather the Initial Idea, Step 2: Research the Topic on…, Step 3: Research the Codebase and Step 4: Synthesize the…, plus 4 more sections
  • Calls gh

What it does

Create Issue With Websearch is an agent skill from dyoshikawa/rulesync. Create a GitHub issue from a vague idea by thoroughly researching the topic on the web to sharpen the specification before filing

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development. It works with GitHub. The repository describes itself as: A Utility CLI for AI Coding Agents. The licence is MIT.

When your agent uses it

  • Development work in your project

Example prompts

  • “/create-issue-with-websearch”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Gather the Initial Idea
  2. Research the Topic on the Web
  3. Research the Codebase
  4. Synthesize the Specification
  5. Draft the Issue
  6. Assign Labels
  7. Create the Issue
  8. Report Result

What it can do on your machine

Read from SKILL.md and the folder at commit 2c577d0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gh

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gh, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Create Issue With Websearch loads about 1.8k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 874 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from dyoshikawa/rulesync at commit 2c577d0, republished under its MIT licence (© dyoshikawa). 874 words, ~1,807 tokens.

Download SKILL.mdSave it as .claude/skills/create-issue-with-websearch/SKILL.md (or your agent's skills folder).
name
create-issue-with-websearch
description
Create a GitHub issue from a vague idea by thoroughly researching the topic on the web to sharpen the specification before filing
targets
*

topic = the user's request

Use this skill when the user only has a rough, fuzzy idea and needs heavy web research to clarify the target specification before creating an issue. If the user already has a concrete, well-scoped task in mind, use the create-issue skill instead.

Step 1: Gather the Initial Idea

Receive the topic from topic or the user's description.

If the input is very sparse, ask the user just enough to anchor the research:

  • What is the rough area or goal? (e.g., a tool to support, a feature to add, a behavior to change)
  • Why do they want it — what problem or limitation triggered the idea?
  • Any hard constraints known up front (must/must-not, scope boundaries)?

Do not push for full specification details at this stage. The point of this skill is to resolve the unknowns through research, not to force the user to resolve them manually.

Step 2: Research the Topic on the Web

Investigate the topic thoroughly using WebSearch and WebFetch. The goal is to raise the resolution of the specification until concrete, defensible design decisions become possible.

Look for, as applicable to the topic:

  • Official documentation of any tool, standard, protocol, or API involved — prefer primary sources over blog posts.
  • File formats, configuration schemas, naming conventions, and default locations used by the target tool(s).
  • Feature support matrices: project vs. global scope, supported file types, known limitations.
  • Recent changes, deprecations, or pre-release behavior that might affect the design.
  • Prior art: how similar tools or competing implementations solve the same problem.
  • Existing discussions (GitHub issues, release notes, RFCs) that reveal open questions or community expectations.

Guidelines while researching:

  • Run multiple searches in parallel when the angles are independent.
  • Cross-check claims against at least one primary source before relying on them.
  • Capture exact URLs, version numbers, and quoted snippets as you go — they will be cited in the issue.
  • If a source disagrees with another, note the disagreement explicitly rather than silently picking one side.
  • Stop expanding research once the open questions needed to draft the issue are answered; avoid rabbit holes unrelated to the decision.

Step 3: Research the Codebase

With the web findings in hand, investigate the relevant parts of this repository to ground the issue in the real code:

  • Which files, modules, or conventions are affected?
  • How do existing, analogous features handle the same concerns (scope, frontmatter, generated output, tests)?
  • Which project-specific rules apply (see CLAUDE.md, .claude/rules/**, docs/**)?

Prefer targeted symbol and search tools over reading whole files.

Step 4: Synthesize the Specification

Before drafting, write down internally:

  • The sharpened problem statement (one or two sentences).
  • The concrete proposal — scope, interfaces, file layout, defaults — as resolved by the research.
  • Open questions that research could not close, stated as explicit unknowns.
  • Trade-offs and the reasoning behind the chosen direction.

If, after research, the idea still cannot be pinned down to an actionable proposal, stop and report this to the user instead of filing a vague issue.

Step 5: Draft the Issue

All issue content (title, body, labels) must be written in English, regardless of the conversation language.

Use this structure:

markdown
## Summary

A concise one-liner describing the sharpened proposal.

## Motivation / Purpose

The problem or opportunity, grounded in what the research revealed (user impact, missing capability, spec gap, etc.).

## Background from Research

Key findings from the web research that shape the proposal. Keep it tight, but every non-trivial factual claim must be backed by an inline link to its source (e.g., `[official docs](https://...)`). Include exact version numbers where relevant. Do not paraphrase a source without linking to it.

## Proposed Specification

The concrete plan the research supports:

- Behavior and scope (project / global, supported inputs, outputs)
- File formats, paths, frontmatter, and defaults
- Interactions with existing features in this repo
- Acceptance criteria / expected behavior

## Open Questions

Unresolved points that need a maintainer decision, each phrased as a concrete question with the options considered.

## References

Bulleted list of the primary sources used, with links.
Show full SKILL.md (361 more words)Show less
Reference URL Requirements

The References section is mandatory — an issue created by this skill must never ship without it. Follow these rules:

  • List every URL consulted during research that materially shaped the proposal, not just the top one or two. Err on the side of including more.
  • Use full, clickable URLs (e.g., https://example.com/docs/foo). Do not shorten, redirect, or paraphrase the link target.
  • Annotate each entry with a short description so the reader understands why it is cited (e.g., - https://example.com/docs/foo — official schema reference for the foo config).
  • Prefer primary sources (official docs, specs, source code, release notes, RFCs) over blog posts or AI-generated summaries. If a secondary source is cited, pair it with the primary source it references.
  • Include version numbers, commit SHAs, or access dates when the page is likely to change (e.g., pre-release docs, changelogs, main-branch source links).
  • When a claim in Background from Research or Proposed Specification comes from a specific source, link to it inline as well — the References section lists all sources, but the inline links make it auditable which claim came from where.
  • If research yielded no usable external sources, say so explicitly in References rather than omitting the section — this signals that the proposal rests on codebase inspection and maintainer judgement alone.

Be faithful to the research: do not assert behavior that was not confirmed. If a claim is inferred rather than verified, label it as such.

Step 6: Assign Labels

Fetch the repository label vocabulary and choose from it — do not invent labels:

bash
gh label list

Pick a small, precise set (usually 1–3). Typical combinations for this skill:

  • A type label such as enhancement, documentation, or question.
  • considering when the proposal is worth discussing but not yet accepted — common for issues created via this skill, since the spec was just sharpened and may still need maintainer sign-off.
  • good first issue only if the final proposal is small, well-scoped, and approachable for newcomers. Fuzzy, research-heavy issues usually are not.

Step 7: Create the Issue

bash
gh issue create --title "<concise title>" --body "<drafted body>" --label "<label1>,<label2>,..."

Step 8: Report Result

Output:

  • The created issue URL
  • Issue title and assigned labels
  • A short list of the most important research sources used
  • Any open questions that remain for the maintainer to decide

© dyoshikawa, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .rulesync/skills/create-issue-with-websearch of dyoshikawa/rulesync.

Open the folder on GitHubat commit 2c577d0

Compare with similar skills

Create Issue With Websearch next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Create Issue With Websearch compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Create Issue With Websearch this skilldyoshikawa/rulesync1.5k—~1.8kAutomated safety check: PassMIT
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Greplooponyx-dot-app/onyx32k4 repos~3.3kAutomated safety check: PassMIT
Check PRonyx-dot-app/onyx32k2 repos~2.3kAutomated safety check: PassMIT
Setup Matt Pocock Skillsbestofjs/bestofjs3.1k20 repos~1.7kAutomated safety check: PassMIT
Contributor-First PR MergeHKUDS/OpenHarness16k1 repos~847Automated safety check: PassMIT

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Works with

Categories

Questions about Create Issue With Websearch

What does Create Issue With Websearch do?

Create a GitHub issue from a vague idea by thoroughly researching the topic on the web to sharpen the specification before filing. Create Issue With Websearch is an agent skill from dyoshikawa/rulesync.

When should I use Create Issue With Websearch?

Create Issue With Websearch fits situations like: development work in your project.

How do I install Create Issue With Websearch in Claude Code?

Run `npx skills add dyoshikawa/rulesync --skill create-issue-with-websearch -a claude-code`. Or copy the skill folder (.rulesync/skills/create-issue-with-websearch in dyoshikawa/rulesync) into .claude/skills/create-issue-with-websearch in your project. Claude Code loads it when a task matches its description.

How do I install Create Issue With Websearch in Codex?

Run `npx skills add dyoshikawa/rulesync --skill create-issue-with-websearch -a codex`. Or copy the skill folder (.rulesync/skills/create-issue-with-websearch in dyoshikawa/rulesync) into .agents/skills/create-issue-with-websearch in your project. Codex loads it when a task matches its description.

Can I use Create Issue With Websearch in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add dyoshikawa/rulesync --skill create-issue-with-websearch -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/create-issue-with-websearch, .gemini/skills/create-issue-with-websearch, .github/skills/create-issue-with-websearch and .opencode/skills/create-issue-with-websearch in your project.

What does Create Issue With Websearch need to run?

Going by SKILL.md and its folder, Create Issue With Websearch needs the command-line tools its instructions call (gh).

Does Create Issue With Websearch access the network?

SKILL.md contains no URLs. Its commands use gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Create Issue With Websearch safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Create Issue With Websearch use?

Create Issue With Websearch is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Create Issue With Websearch use?

About 1.8k tokens (SKILL.md is roughly 7.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Create Issue With Websearch?

Skills that share tags, products or a category with Create Issue With Websearch: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Greploop (onyx-dot-app/onyx, 32k stars), Check PR (onyx-dot-app/onyx, 32k stars) and Setup Matt Pocock Skills (bestofjs/bestofjs, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Create Issue With Websearch?

dyoshikawa (a GitHub user) maintains it in dyoshikawa/rulesync, which has 1,508 GitHub stars. The repository holds 40 skills in this directory. The repository was last updated on October 9, 2026.

Source: dyoshikawa/rulesync on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.