resolving-issue — for Claude Code resolving-issue, community, for Claude Code, ide skills, markdown, AGENTS.md, ## Type, feature, refactor, ## Step 3 — Implement Follow

v1.0.0

Acerca de este Skill

Escenario recomendado: Ideal for AI agents that need implementing issue. Resumen localizado: Markdown section numbers checker # Implementing Issue Read AGENTS.md for architecture conventions and docs/CONTRIBUTING.md for branch/commit/PR rules. It covers cli, markdown, rust workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Características

Implementing Issue
Read AGENTS.md for architecture conventions and docs/CONTRIBUTING.md for branch/commit/PR rules.
Also read docs/PATTERNS.md, docs/TESTING.md, and docs/VALIDATION.md before implementing.
Step 0 — Read the Issue
Determine the issue number from the user's message or context. Fetch the Issue:

# Core Topics

23prime 23prime
[0]
[0]
Updated: 3/30/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 8/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
8/11
Quality Score
46
Canonical Locale
en
Detected Body Locale
en

Escenario recomendado: Ideal for AI agents that need implementing issue. Resumen localizado: Markdown section numbers checker # Implementing Issue Read AGENTS.md for architecture conventions and docs/CONTRIBUTING.md for branch/commit/PR rules. It covers cli, markdown, rust workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

¿Por qué usar esta habilidad?

Recomendacion: resolving-issue helps agents implementing issue. Markdown section numbers checker # Implementing Issue Read AGENTS.md for architecture conventions and docs/CONTRIBUTING.md for branch/commit/PR rules.

Mejor para

Escenario recomendado: Ideal for AI agents that need implementing issue.

Casos de uso accionables for resolving-issue

Caso de uso: Applying Implementing Issue
Caso de uso: Applying Read AGENTS.md for architecture conventions and docs/CONTRIBUTING.md for branch/commit/PR rules
Caso de uso: Applying Also read docs/PATTERNS.md, docs/TESTING.md, and docs/VALIDATION.md before implementing

! Seguridad y limitaciones

  • Limitacion: Conventional Commits, English only
  • Limitacion: Create a PR following .github/PULL REQUEST TEMPLATE.md. PR body must be in English and include Closes #<N .
  • Limitacion: PR body must be in English and include Closes #<N

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is resolving-issue?

Escenario recomendado: Ideal for AI agents that need implementing issue. Resumen localizado: Markdown section numbers checker # Implementing Issue Read AGENTS.md for architecture conventions and docs/CONTRIBUTING.md for branch/commit/PR rules. It covers cli, markdown, rust workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install resolving-issue?

Run the command: npx killer-skills add 23prime/mdsn/resolving-issue. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for resolving-issue?

Key use cases include: Caso de uso: Applying Implementing Issue, Caso de uso: Applying Read AGENTS.md for architecture conventions and docs/CONTRIBUTING.md for branch/commit/PR rules, Caso de uso: Applying Also read docs/PATTERNS.md, docs/TESTING.md, and docs/VALIDATION.md before implementing.

Which IDEs are compatible with resolving-issue?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for resolving-issue?

Limitacion: Conventional Commits, English only. Limitacion: Create a PR following .github/PULL REQUEST TEMPLATE.md. PR body must be in English and include Closes #<N .. Limitacion: PR body must be in English and include Closes #<N.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add 23prime/mdsn/resolving-issue. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use resolving-issue immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

resolving-issue

Install resolving-issue, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Implementing Issue

Read AGENTS.md for architecture conventions and docs/CONTRIBUTING.md for branch/commit/PR rules. Also read docs/PATTERNS.md, docs/TESTING.md, and docs/VALIDATION.md before implementing.

Step 0 — Read the Issue

Determine the issue number from the user's message or context. Fetch the Issue:

bash
1REPO=$(gh repo view --json nameWithOwner --jq .nameWithOwner) 2gh issue view <N> -R "$REPO"

Read the title, body, and comments to understand the task fully before proceeding.

The Issue body follows .github/ISSUE_TEMPLATE/default.md. Extract the Type field from the ## Type section if present.

Step 1 — Clarify task type

Use the Type extracted from the Issue body. If the ## Type section is missing or unclear, determine the type from context:

TypeBranch prefixCommit type
featfeature/feat
fixfeature/fix
refactorfeature/refactor
perffeature/perf
docsfeature/docs
aifeature/ai
chorefeature/chore

Confirm the task and type with the user before proceeding.

Step 2 — Create branch

Include the Issue number in the branch name:

bash
1git switch -c feature/<N>-<short-description>

Step 3 — Implement

Follow AGENTS.md conventions. Consult the docs before writing code:

  • docs/PATTERNS.md — source layout, how to add a rule, clap and output patterns
  • docs/TESTING.md — test structure, helper patterns, DirGuard
  • docs/VALIDATION.md — layer boundaries and what each layer validates

Step 4 — Update docs/SPEC.md if needed

If the implementation changes user-visible behavior (new flags, new error codes, output format changes, new validation rules), update docs/SPEC.md accordingly.

Step 5 — Test against real files

bash
1mise run rs-run -- -- 'examples/*.md'

Step 6 — Auto-fix and check

bash
1mise run fix

If any errors remain that cannot be auto-fixed, resolve them manually, then verify:

bash
1mise run check

Repeat until clean.

Step 7 — CodeRabbit review

Invoke the coderabbit skill. Fix each actionable finding and re-review until clean.

Step 8 — Commit

Follow docs/CONTRIBUTING.md:

  • Conventional Commits, English only
  • No Co-Authored-By: line
bash
1git add <files> 2git commit -m "<type>: <description>"

Step 9 — Push and open PR

bash
1git push -u origin feature/<N>-<short-description>

Create a PR following .github/PULL_REQUEST_TEMPLATE.md. PR body must be in English and include Closes #<N>.

bash
1gh pr create --title "<type>: ..." --body "$(cat <<'EOF' 2## Checklist 3 4- [ ] Target branch is `main` 5- [ ] Status checks are passing 6 7## Summary 8 9## Reason for change 10 11## Changes 12 13## Notes 14 15Closes #<N> 16EOF 17)"

Step 10 — Address PR review comments

After opening the PR, GitHub Copilot and CodeRabbit will post review comments automatically. Check whether reviews have arrived:

bash
1gh pr view <PR_NUMBER> --json reviews | jq '[.reviews[].author.login]'
  • If the array is empty, reviews have not arrived yet. Wait ~2–3 minutes and check again.
  • If still empty after ~5 minutes, automated reviews are likely disabled — skip this step.
  • If copilot-pull-request-reviewer or coderabbitai appear, invoke the implementing-pr-review skill to evaluate and apply valid suggestions.

Step 11 — Reflect learnings into docs/

After the PR is merged, review what was encountered during implementation and PR review. If anything is generalizable — useful for future implementations in this project — add it to the appropriate file under docs/.

Sources to review:

  • Accepted review comments: patterns or pitfalls that reviewers pointed out
  • User corrections: when the user said "no, not that — do X instead", consider whether X is a project-wide rule worth documenting
  • Compilation/check failures: if mise run check failed for a non-obvious reason, note the fix

Choose the target file based on the nature of the learning:

Learning typeTarget file
Code patterns, clap/serde conventions, output formattingdocs/PATTERNS.md
Test structure, helper patterns, working directory gotchasdocs/TESTING.md
Validation boundary decisions, try_new vs newdocs/VALIDATION.md

Criteria for adding:

  • Would a future implementer likely make the same mistake?
  • Is it specific to this codebase (not just "read the Rust docs")?
  • Is it concrete enough to be actionable?

If any of the above apply, open a separate PR for the docs updates:

bash
1git switch main && git pull 2git switch -c docs/patterns-from-issue-<N> 3git add docs/ 4git commit -m "docs: add patterns from issue-<N> implementation" 5git push -u origin docs/patterns-from-issue-<N> 6gh pr create --title "docs: add patterns from issue-<N> implementation" --body "$(cat <<'EOF' 7## Checklist 8 9- [ ] Target branch is `main` 10- [ ] Status checks are passing 11 12## Summary 13 14Add generalizable patterns learned during issue-<N> implementation. 15 16## Notes 17 18Related: #<PR_NUMBER> 19EOF 20)"

If nothing generalizable was found, skip this step.

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