---
name: ln-914-community-responder
description: "Responds to unanswered GitHub discussions and issues with codebase-informed replies. Use when clearing community question backlog."
disable-model-invocation: true
license: MIT
allowed-tools: Read, Grep, Glob, Bash, WebFetch
---

> **Paths:** File paths (`shared/`, `references/`, `../ln-*`) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root. If `shared/` is missing, fetch files via WebFetch from `https://raw.githubusercontent.com/levnikolaevich/claude-code-skills/master/skills/{path}`.

# ln-914-community-responder

**Type:** L3 Worker (standalone)
**Category:** 9XX Community Engagement
Responds to unanswered GitHub Discussions and Issues by analyzing the question, searching the codebase for answers, and composing a helpful reply. Supports single-item and batch modes.

---

## Overview

| Aspect | Details |
|--------|---------|
| **Input** | `$ARGUMENTS`: discussion/issue number (`#42`), `batch` (all unanswered P1), or empty (interactive) |
| **Output** | Response comment(s) published to GitHub |
| **Pattern** | Read question → Search codebase → Compose response → Fact-check → Publish |

---

## Phase 0: GitHub Discovery

**MANDATORY READ:** Load `shared/references/community_github_discovery.md`

Execute the discovery protocol. Extract:
- `{owner}/{repo}` for URLs and API calls
- `repo.id` for GraphQL mutations
- `maintainer` login (authenticated user)
- Discussion category IDs

Load strategy: check `docs/community_engagement_strategy.md` in target project, fallback to `shared/references/community_strategy_template.md`. Extract Section 5 (Engagement Metrics) and Section 6 (Tone Guide).

**MANDATORY READ:** Load `shared/references/community_discussion_formatting.md`
**MANDATORY READ:** Load [response_styles.md](references/response_styles.md)
**MANDATORY READ:** Load `shared/references/humanizer_checklist.md`

---

## Phase 1: Load Items

### Single Item Mode

If `$ARGUMENTS` contains a number (e.g., `42`, `#42`):

```bash
# For discussions
gh api graphql -f query='query($owner: String!, $name: String!) {
  repository(owner: $owner, name: $name) {
    discussion(number: {N}) {
      id number title body
      category { name }
      author { login }
      createdAt
      answerChosenAt
      comments(first: 20) {
        totalCount
        nodes { author { login } body createdAt }
      }
    }
  }
}' -f owner="{owner}" -f name="{repo}"
```

```bash
# For issues (if discussion not found)
gh issue view {N} --repo {owner}/{repo} --json number,title,body,author,createdAt,comments,labels
```

### Batch Mode

If `$ARGUMENTS` is `batch`:

1. Fetch recent discussions + issues via GraphQL (last 30 days, open, sorted by created DESC)
2. Filter to P1 items: author != maintainer AND zero maintainer comments
3. Fetch full context for each item (max 10 per batch)

### Interactive Mode

If `$ARGUMENTS` is empty, list recent unanswered items and ask the user which to respond to.

---

## Phase 2: Analyze Context

For each item:

### 2a. Understand the Question

1. Read the discussion/issue body — identify the core question or problem
2. Read existing comments — check if partially answered or if follow-ups changed the scope
3. Detect item type: Q&A question, bug report, feature request, configuration help, general feedback

### 2b. Search Codebase for Answer

Based on the question type, search for relevant information:

| Question Type | Search Strategy |
|---------------|----------------|
| "How do I..." | Grep for keywords in SKILL.md files, README.md, docs/ |
| Bug report | Grep for mentioned function/file, check git log for recent fixes |
| Configuration | Read .hex-skills/environment_state.json, CLAUDE.md, relevant SKILL.md |
| Feature request | Check if feature already exists, grep for related patterns |
| Installation | Read README.md installation section, plugin.json |

```
FOR each item:
  1. Extract keywords from question (function names, skill names, error messages)
  2. Grep codebase for keywords (max 5 searches)
  3. Read relevant files (max 3 files, prioritize SKILL.md and docs/)
  4. Check git log for recent changes related to the topic
  5. If answer found → proceed to Phase 3
  6. If not found → mark as "needs-manual" and suggest the user respond directly
```

### 2c. Detect First-Time Poster

```bash
gh api graphql -f query='query($owner: String!, $name: String!) {
  repository(owner: $owner, name: $name) {
    discussions(first: 100) {
      nodes { author { login } }
    }
  }
}' -f owner="{owner}" -f name="{repo}"
```

Count how many discussions the author has created. If 0 previous (this is their first) → flag for Welcome style.

---

## Phase 3: Classify Response Type

**MANDATORY READ:** Load [response_styles.md](references/response_styles.md) — use the classification matrix.

| Item Type | Response Style |
|-----------|---------------|
| Q&A question with answer found | **Technical Answer** |
| Bug report | **Bug Acknowledgment** |
| Feature request / idea | **Feature Acknowledgment** |
| Question already answered elsewhere | **Redirect** |
| First-time poster (any type) | **Welcome** + appropriate content style |
| Stale item with progress update | **Status Update** |
| Cannot find answer in codebase | Mark `needs-manual` — skip composition |

---

## Phase 4: Compose Response

Use the selected style template from `response_styles.md`.

### Required Elements (All Styles)

- **Thank the author** — by name if possible, acknowledge their contribution
- **Answer the question** — direct, clear, linked to source code/docs
- **Invite follow-up** — "Let us know if this helps" or similar
- **No jargon without context** — explain internal terms
- **Link to code** — at least one link to relevant file in the repo

### Batch Mode Composition

In batch mode, compose all responses first, then present ALL for user review before publishing any.

---

## Phase 5: Fact-Check

Before presenting to user, verify every claim:

1. **File paths & links** — verify each linked file exists: `ls {path}`
2. **Code references** — verify mentioned functions/classes exist: `grep -r "{name}"`
3. **Feature descriptions** — re-read source file, confirm accuracy
4. **Install/usage commands** — verify against README.md

5. **Humanizer audit** -- run the audit protocol from `humanizer_checklist.md`. If 3+ AI patterns found, rewrite flagged sections.

**Gate:** If any check fails, fix the response before proceeding.

---

## Phase 6: Review and Publish

### Single Item Mode

Present the composed response to the user. **Wait for explicit approval before publishing.**

### Batch Mode

Present ALL responses in a summary table:

```
### Batch Responses — {N} items

| # | Type | Title | Style | Status |
|---|------|-------|-------|--------|
| {number} | {Discussion/Issue} | {title} | {Technical/Bug/Welcome/...} | Ready |
| {number} | ... | ... | ... | needs-manual |
```

Then show each response body. User can approve all, approve selectively, or edit individual responses.

### Publish Discussion Comment

```bash
gh api graphql -f query='
  mutation($discussionId: ID!, $body: String!) {
    addDiscussionComment(input: {
      discussionId: $discussionId,
      body: $body
    }) {
      comment { url }
    }
  }
' -f discussionId="{discussion.id}" -f body="{response body}"
```

### Publish Issue Comment

```bash
gh issue comment {number} --repo {owner}/{repo} --body "{response body}"
```

Report the comment URL(s) to the user.

---

## Rules

- **Always require user approval** before publishing any response
- **Never close** discussions or issues — only respond
- **Never mark as answered** — let the author do it (for Q&A discussions)
- **Batch limit:** max 10 items per batch (prevent context overload)
- **needs-manual items:** report to user with GitHub URL + reason, do not attempt response
- **Tone:** per strategy Section 6 — respectful, helpful, link to code

---

## Definition of Done

- [ ] Items loaded (single, batch, or interactive selection)
- [ ] Question context analyzed + codebase searched for answers
- [ ] Response type classified per response_styles.md
- [ ] First-time posters detected and welcomed
- [ ] Response(s) composed with links to relevant code/docs
- [ ] Fact-checked (file paths, code references, commands verified)
- [ ] User approved response(s)
- [ ] Published via GraphQL/CLI, comment URL(s) reported
- [ ] needs-manual items reported to user with URLs

---

**Version:** 1.0.0
**Last Updated:** 2026-03-14


---
Source attribution: boisenoise
Original project: https://github.com/boisenoise/skills-collections/blob/main/skills/levn-ln-914-community-responder/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: boisenoise
Original project: https://github.com/boisenoise/skills-collections/blob/main/skills/levn-ln-914-community-responder/SKILL.md
Attribution basis: Source repository record

Fields of work: Content & Media, Customer Support
Roles: Community Manager, Support Agent, Technical Writer
Specialties: API
Tools: GitHub
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: b1a641de6b8a6104ce7ebfde0ab5624f39d488d71986a1f7a29fffe3aa0dd32a