answer-slack

name	answer-slack
description	Fetches Slack thread context, researches the topic using agent skills and MCP tools, and presents findings for the user to decide on a reply. Use when given a Slack message permalink to understand and respond to a conversation.
disable-model-invocation	true

Answer Slack

Given a Slack message link, fetch the conversation context, analyse the topic, research using relevant agent skills and MCP tools, and present findings to the user. The user digests the information and decides whether to ask for a Slack reply draft.

Input

A Slack message permalink in the form:

https://<workspace>.slack.com/archives/<channel_id>/p<ts_without_dot>

Steps

0. Recommended mode: Ask

Require Ask mode following the mode-gate skill. This command is primarily informational -- it researches a Slack conversation and presents findings without making changes. If the user later wants to post a Slack reply (step 7), they should switch to Agent mode for that.

1. Parse the Slack link

Extract channel_id and reconstruct thread_ts from the URL:

• channel_id is the path segment after /archives/.
• thread_ts is derived from the p-prefixed timestamp by inserting a dot before the last 6 digits (e.g. p1234567890123456 becomes 1234567890.123456).

If the link is malformed or missing, ask the user and stop.

2. Fetch message context

• Call slack_get_thread_replies with the extracted channel_id and thread_ts to retrieve the full thread.
• If the message has no thread replies, fall back to slack_get_channel_history scoped around the timestamp to capture surrounding messages.
• Resolve participant names by calling slack_get_user_profile for each unique user ID that appears in the messages.

3. Follow embedded links

Scan the messages for links to external resources and fetch each one to build a complete picture:

Link type	How to resolve
Slack message permalink (/archives/<channel>/p<ts>)	Parse the link (same logic as step 1) and call slack_get_thread_replies to pull that thread
Azure DevOps work item (_workitems/edit/<id>)	Extract the ID and fetch via get_work_item
Azure DevOps pull request (_git/<repo>/pullrequest/<id>)	Extract the ID and fetch via get_pr_details
Azure DevOps build / pipeline (_build/results?buildId=<id>)	Extract the ID and fetch via get_build_details
Datadog incident or monitor URL	Extract the ID and fetch via the Datadog MCP tools
GitHub PR or issue	Extract the owner/repo/number and fetch via gh CLI or GitHub MCP
Generic URL	Fetch with WebFetch if the content is likely to add useful context

Stop recursing when a linked resource doesn't itself contain further actionable links, or when the same resource has already been fetched.

4. Analyse the conversation

Read the thread and determine:

• What is being asked or discussed -- the core question, request, or topic.
• Who is asking -- the person(s) expecting a response.
• Domain -- which area the message touches (code, incident, build failure, process, tooling, general discussion, etc.).
• Urgency -- whether the tone or context suggests time pressure.
• Whether a response is expected from the user -- some threads are informational; not all require a reply.

5. Select and apply relevant artifacts

Based on the domain identified in step 4, use the appropriate agent skills and MCP tools to research. Explain which skills were selected and why.

Domain	Artifacts / tools to consider
Code questions	Search the codebase; apply the functional-typescript skill for TypeScript questions
Incidents	Follow the incident-response skill's investigation structure; query Datadog via MCP
Build failures	Follow the triage-build skill's investigation pattern; query Azure DevOps and Currents via MCP
Work items	Fetch details from Azure DevOps via MCP
Process / tooling	Search existing commands and skills for relevant guidance
General	Research using available MCP tools and codebase search

When a topic spans multiple domains, investigate each relevant angle.

6. Present findings

Present a structured summary to the user (not as a Slack message draft):

## Slack Thread: <channel name> -- <brief topic>

**From**: <who asked> | **Domain**: <domain> | **Response expected**: yes / no

### Context

<concise summary of the conversation so far>

### Research

<findings from step 5 -- evidence, code references, data points>

### Suggested Answer Direction

<bullet points outlining what a good reply would cover, without composing the reply itself>

7. Offer to draft a reply

After presenting findings, offer to compose a Slack reply. If the user accepts:

1. Read and apply the external-communications skill, then draft the reply following it and the objective-communication skill.
2. Present the draft for approval.
3. Post via slack_reply_to_thread only after explicit approval.

Wait for user confirmation before taking any action.

8. Evolve

Follow the continuous-improvement skill.