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External Comms

CommunityPopular
bradygaster
external-comms

Workflow for scanning, drafting, and presenting community responses with a human review gate

Overview

Publisherbradygaster
Repositorysquad
Skill nameexternal-comms
Stars
3.3K
Forks
506
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by bradygaster on GitHub. Read the source before you install it.

Installation

Install the External Comms AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/bradygaster/squad/tree/dev/packages/squad-cli/templates/skills/external-comms
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bradygaster/squad.git /tmp/squad
mkdir -p .claude/skills
cp -r /tmp/squad/packages/squad-cli/templates/skills/external-comms .claude/skills/external-comms
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable External Comms in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads External Comms on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so External Comms is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Context

Phase 1 is draft-only mode.

  • The communications owner scans issues and discussions, drafts responses with the humanizer skill, and presents a review table for human approval.
  • Human review gate is mandatory — the communications owner never posts autonomously.
  • Every action is logged to .squad/comms/audit/.
  • This workflow is triggered manually only ("check community") — no automated activation in Phase 1.

Patterns

1. Scan

Find unanswered community items with GitHub MCP tools first, or gh issue list / gh api as fallback for issues and discussions.

  • Include open issues and discussions only.
  • Filter for items with no squad team response.
  • Limit to items created in the last 7 days.
  • Exclude items labeled squad:internal or wontfix.
  • Include discussions and issues in the same sweep.
  • Phase 1 scope is issues and discussions only — do not draft PR replies.

Discussion Handling (Phase 1)

Discussions use the GitHub Discussions API, which differs from issues:

  • Scan: gh api /repos/{owner}/{repo}/discussions --jq '.[] | select(.answer_chosen_at == null)' to find unanswered discussions
  • Categories: Filter by Q&A and General categories only (skip Announcements, Show and Tell)
  • Answers vs comments: In Q&A discussions, the communications owner drafts an "answer" (not a comment). The human marks it as accepted answer after posting.
  • Phase 1 scope: Issues and Discussions ONLY. No PR comments.

2. Classify

Determine the response type before drafting.

  • Welcome (new contributor)
  • Troubleshooting (bug/help)
  • Feature guidance (feature request/how-to)
  • Redirect (wrong repo/scope)
  • Acknowledgment (confirmed, no fix)
  • Closing (resolved)
  • Technical uncertainty (unknown cause)
  • Empathetic disagreement (pushback on a decision or design)
  • Information request (need more reproduction details or context)

Template Selection Guide

Signal in Issue/Discussion→ Response TypeTemplate
New contributor (0 prior issues)WelcomeT1
Error message, stack trace, "doesn't work"TroubleshootingT2
"How do I...?", "Can Squad...?", "Is there a way to...?"Feature GuidanceT3
Wrong repo, out of scope for SquadRedirectT4
Confirmed bug, no fix available yetAcknowledgmentT5
Fix shipped, PR merged that resolves issueClosingT6
Unclear cause, needs investigationTechnical UncertaintyT7
Author disagrees with a decision or designEmpathetic DisagreementT8
Need more reproduction info or contextInformation RequestT9

Use exactly one template as the base draft. Replace placeholders with issue-specific details, then apply the humanizer patterns. If the thread spans multiple signals, choose the highest-risk template and capture the nuance in the thread summary.

Confidence Classification

ConfidenceCriteriaExample
🟢 HighAnswer exists in Squad docs or FAQ, similar question answered before, no technical ambiguity"How do I install Squad?"
🟡 MediumTechnical answer is sound but involves judgment calls, OR docs exist but don't perfectly match the question, OR tone is tricky"Can Squad work with Azure DevOps?" (yes, but setup is nuanced)
🔴 Needs ReviewTechnical uncertainty, policy/roadmap question, potential reputational risk, author is frustrated/angry, question about unreleased features"When will Squad support Claude?"

Auto-escalation rules:

  • Any mention of competitors → 🔴
  • Any mention of pricing/licensing → 🔴
  • Author has >3 follow-up comments without resolution → 🔴
  • Question references a closed-wontfix issue → 🔴

3. Draft

Use the humanizer skill for every draft.

  • Complete Thread-Read Verification before writing.
  • Read the full thread, including all comments, before writing.
  • Select the matching template from the Template Selection Guide and record the template ID in the review notes.
  • Treat templates as reusable drafting assets: keep the structure, replace placeholders, and only improvise when the thread truly requires it.
  • Validate the draft against the humanizer anti-patterns.
  • Flag long threads (>10 comments) with ⚠️.

Thread-Read Verification

Before drafting, the communications owner MUST verify complete thread coverage:

  1. Count verification: Compare API comment count with actually-read comments. If mismatch, abort draft.
  2. Deleted comment check: Use gh api timeline to detect deleted comments. If found, flag as ⚠️ in review table.
  3. Thread summary: Include in every draft: "Thread: {N} comments, last activity {date}, {summary of key points}"
  4. Long thread flag: If >10 comments, add ⚠️ to review table and include condensed thread summary
  5. Evidence line in review table: Each draft row includes "Read: {N}/{total} comments" column

4. Present

Show drafts for review in this exact format:

text
📝 Community Response Drafts
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

| # | Item | Author | Type | Confidence | Read | Preview |
|---|------|--------|------|------------|------|---------|
| 1 | Issue #N | @user | Type | 🟢/🟡/🔴 | N/N | "First words..." |

Confidence: 🟢 High | 🟡 Medium | 🔴 Needs review

Full drafts below ▼

Each full draft must begin with the thread summary line: Thread: {N} comments, last activity {date}, {summary of key points}

5. Human Action

Wait for explicit human direction before anything is posted.

  • comms approve 1 3 — approve drafts 1 and 3
  • comms edit 2 — edit draft 2
  • comms skip — skip all
  • banana — freeze all pending (safe word)

Rollback — Bad Post Recovery

If a posted response turns out to be wrong, inappropriate, or needs correction:

  1. Delete the comment:
    • Issues: gh api -X DELETE /repos/{owner}/{repo}/issues/comments/{comment_id}
    • Discussions: gh api graphql -f query='mutation { deleteDiscussionComment(input: {id: "{node_id}"}) { comment { id } } }'
  2. Log the deletion: Write audit entry with action delete, include reason and original content
  3. Draft replacement (if needed): The communications owner drafts a corrected response and repeats the normal review cycle
  4. Postmortem: If the error reveals a pattern gap, update humanizer anti-patterns or add a new test case

Safe word — banana:

  • Immediately freezes all pending drafts in the review queue
  • No new scans or drafts until comms resume is issued
  • Audit entry logged with halter identity and reason

6. Post

After approval:

  • Human posts via gh issue comment for issues or gh api for discussion answers/comments.
  • The communications owner helps by preparing the CLI command.
  • Write the audit entry after the posting action.

7. Audit

Log every action.

  • Location: .squad/comms/audit/{timestamp}.md
  • Required fields vary by action — see .squad/comms/templates/audit-entry.md Conditional Fields table
  • Universal required fields: timestamp, action
  • All other fields are conditional on the action type

Examples

These are reusable templates. Keep the structure, replace placeholders, and adjust only where the thread requires it.

Example scan command

bash
gh issue list --state open --json number,title,author,labels,comments --limit 20

Example review table

text
📝 Community Response Drafts
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

| # | Item | Author | Type | Confidence | Read | Preview |
|---|------|--------|------|------------|------|---------|
| 1 | Issue #426 | @newdev | Welcome | 🟢 | 1/1 | "Hey @newdev! Welcome to Squad..." |
| 2 | Discussion #18 | @builder | Feature guidance | 🟡 | 4/4 | "Great question! Today the CLI..." |
| 3 | Issue #431 ⚠️ | @debugger | Technical uncertainty | 🔴 | 12/12 | "Interesting find, @debugger..." |

Confidence: 🟢 High | 🟡 Medium | 🔴 Needs review

Full drafts below ▼

Example audit entry (post action)

markdown
---
timestamp: "2026-03-16T21:30:00Z"
action: "post"
item_number: 426
draft_id: 1
reviewer: "@bradygaster"
---

## Context (draft, approve, edit, skip, post, delete actions)
- Thread depth: 3
- Response type: welcome
- Confidence: 🟢
- Long thread flag: false

## Draft Content (draft, edit, post actions)
Thread: 3 comments, last activity 2026-03-16, reporter hit a preview-build regression after install.

Hey @newdev! Welcome to Squad 👋 Thanks for opening this.
We reproduced the issue in preview builds and we're checking the regression point now.
Let us know if you can share the command you ran right before the failure.

## Post Result (post, delete actions)
https://github.com/bradygaster/squad/issues/426#issuecomment-123456

T1 — Welcome

text
Hey {author}! Welcome to Squad 👋 Thanks for opening this.
{specific acknowledgment or first answer}
Let us know if you have questions — happy to help!

T2 — Troubleshooting

text
Thanks for the detailed report, {author}!
Here's what we think is happening: {explanation}
{steps or workaround}
Let us know if that helps, or if you're seeing something different.

T3 — Feature Guidance

text
Great question! {context on current state}
{guidance or workaround}
We've noted this as a potential improvement — {tracking info if applicable}.

T4 — Redirect

text
Thanks for reaching out! This one is actually better suited for {correct location}.
{brief explanation of why}
Feel free to open it there — they'll be able to help!

T5 — Acknowledgment

text
Good catch, {author}. We've confirmed this is a real issue.
{what we know so far}
We'll update this thread when we have a fix. Thanks for flagging it!

T6 — Closing

text
This should be resolved in {version/PR}! 🎉
{brief summary of what changed}
Thanks for reporting this, {author} — it made Squad better.

T7 — Technical Uncertainty

text
Interesting find, {author}. We're not 100% sure what's causing this yet.
Here's what we've ruled out: {list}
We'd love more context if you have it — {specific ask}.
We'll dig deeper and update this thread.

T8 — Empathetic Disagreement

text
We hear you, {author}. That's a fair concern.

The current design choice was driven by {reason}. We know it's not ideal for every use case.

{what alternatives exist or what trade-off was made}

If you have ideas for how to make this work better for your scenario, we'd love to hear them — open a discussion or drop your thoughts here!

T9 — Information Request

text
Thanks for reporting this, {author}!

To help us dig into this, could you share:
- {specific ask 1}
- {specific ask 2}
- {specific ask 3, if applicable}

That context will help us narrow down what's happening. Appreciate it!

Anti-Patterns

  • ❌ Posting without human review (NEVER — this is the cardinal rule)
  • ❌ Drafting without reading full thread (context is everything)
  • ❌ Ignoring confidence flags (🔴 items need Lead or human review)
  • ❌ Scanning closed issues (only open items)
  • ❌ Responding to issues labeled squad:internal or wontfix
  • ❌ Skipping audit logging (every action must be recorded)
  • ❌ Drafting for issues where a squad member already responded (avoid duplicates)
  • ❌ Drafting pull request responses in Phase 1 (issues/discussions only)
  • ❌ Treating templates like loose examples instead of reusable drafting assets
  • ❌ Asking for more info without specific requests

Frequently asked questions

What does the External Comms AI skill do?

Workflow for scanning, drafting, and presenting community responses with a human review gate

Why use External Comms on TypingMind?

Because you install it once and use it with any model. External Comms is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install External Comms in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bradygaster/squad/tree/dev/packages/squad-cli/templates/skills/external-comms. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use External Comms?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with External Comms?

As many as you like. As long as a model supports skills, you can use External Comms with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the External Comms AI skill free?

Yes. It is published on GitHub by bradygaster under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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