Diagnose Deployment logo

Diagnose Deployment

Organization
microsoft
diagnose-deployment

Surfaces PAC CLI upload errors and Dataverse async operation errors, pattern-matches against a known failure catalog, and optionally auto-fixes identified issues. Use when asked to: "diagnose deployment", "debug deployment", "deployment failed", "show deployment errors", "fix deployment issues", "show upload logs", "why did my deploy fail", or "troubleshoot upload".

Overview

Publishermicrosoft
Repositorypower-platform-skills
Skill namediagnose-deployment
Stars
993
Forks
204
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 microsoft on GitHub. Read the source before you install it.

Installation

Install the Diagnose Deployment 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/microsoft/power-platform-skills/tree/main/plugins/power-pages/skills/diagnose-deployment
  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/microsoft/power-platform-skills.git /tmp/power-platform-skills
mkdir -p .claude/skills
cp -r /tmp/power-platform-skills/plugins/power-pages/skills/diagnose-deployment .claude/skills/diagnose-deployment
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Diagnose Deployment 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 Diagnose Deployment 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 Diagnose Deployment 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.

Plugin check: Run node "${PLUGIN_ROOT}/scripts/check-version.js" — if it outputs a message, show it to the user before proceeding.

diagnose-deployment

Surfaces and pattern-matches deployment errors against a known failure catalog. For each identified error with an available auto-fix, asks explicit user permission before applying any changes. Never auto-applies fixes without confirmation.

Prerequisites

  • Project root with powerpages.config.json
  • PAC CLI installed (will report if missing)

Phases

Phase 1 — Verify Prerequisites and Locate Project

Create all tasks upfront at the start of this phase.

Tasks to create:

  1. "Verify prerequisites and locate project"
  2. "Collect deployment artifacts"
  3. "Surface upload errors"
  4. "Query solution import status"
  5. "Diagnose and categorize findings"
  6. "Offer auto-fixes"
  7. "Present findings summary"

Steps:

  1. Locate project root: search for powerpages.config.json in cwd and parent directories
  2. Check PAC CLI: pac --version (report version or "not installed")
  3. Check PAC CLI auth: pac env who (report environment URL or "not authenticated")
  4. Check Azure CLI: az account show (report subscription or "not logged in")

Auth failures are non-blocking — report them as findings, continue collecting other artifacts.

Phase 1.5 — Ground in current ALM documentation

Reference: ${PLUGIN_ROOT}/references/alm-docs-grounding.md

Cap this step at ~30 seconds. If MCP search / fetch errors out, log a one-line note and continue — this skill must remain runnable offline.

  1. Run microsoft_docs_search with the query: Power Pages deployment errors solution import troubleshooting.
  2. Fetch https://learn.microsoft.com/en-us/power-platform/alm/solution-concepts-alm (and at most one sister page on troubleshooting or known import errors) in parallel via microsoft_docs_fetch.
  3. Extract a one-paragraph summary of what Microsoft Learn currently says about common deployment failures and their resolution. Compare against ${PLUGIN_ROOT}/references/deployment-error-catalog.md and flag any new error patterns not yet captured in the catalog.
  4. Use the summary to inform pattern-matching in Phase 5. If a new pattern is documented on Learn that isn't in the catalog, surface it to the user as a candidate addition rather than silently extending the catalog.

Phase 2 — Collect Deployment Artifacts

Gather all available context:

  1. Read powerpages.config.json — extract siteName, websiteRecordId, compiledPath
  2. Check .powerpages-site/ folder exists
  3. Glob for manifest files: .powerpages-site/*-manifest.yml — list all found, note their environment hostnames
  4. Check if .solution-manifest.json exists (for solution-related diagnostics)
  5. Check if docs/alm/last-import.json exists (for recent import failures)
  6. Check build output: confirm {compiledPath}/ exists and is non-empty

Report: "Found project: {siteName}. Artifacts collected."

Phase 3 — Surface Upload Errors

Re-run pac pages upload-code-site in capture mode to get fresh error output:

bash
pac pages upload-code-site --rootPath "." 2>&1

Note: This intentionally triggers the upload to capture any errors. If the upload succeeds cleanly, that is also a valid diagnostic result ("no errors found").

Capture stdout+stderr as a single string. Pass to scripts/parse-deployment-errors.js:

bash
echo "{escaped-output}" | node "${PLUGIN_ROOT}/scripts/parse-deployment-errors.js"

Parse the JSON findings array. If the upload succeeded with no errors, note this and skip to Phase 5 with an empty findings list.

Phase 4 — Query Solution Import Status

Only run if .solution-manifest.json exists.

  1. Acquire Azure CLI token for environment URL
  2. Check recent async operations (last 24 hours):
    GET {envUrl}/api/data/v9.2/asyncoperations?$filter=statecode eq 3 and statuscode eq 31 and createdon gt {yesterday}&$select=asyncoperationid,name,message,friendlymessage,statuscode,completedon&$orderby=completedon desc&$top=5
  3. Check recent import jobs:
    GET {envUrl}/api/data/v9.2/importjobs?$select=solutionname,completedon,progress&$orderby=completedon desc&$top=3
  4. If failed operations found, pass each message field through parse-deployment-errors.js

Skip gracefully if auth is not available (auth failure in Phase 1).

Phase 5 — Auto-Diagnose Known Issues

Consolidate all findings from Phases 3 and 4. For each finding, categorize:

  • Error: Blocks deployment
  • Warning: May cause issues
  • Info: Informational

Also add findings for missing artifacts discovered in Phase 2:

  • Missing websiteRecordId → Error (patternId: missing-website-record-id)
  • Empty build output → Error (patternId: empty-build)
  • Multiple environment manifests → Warning (may indicate environment confusion)

Present all findings in a table:

#SeverityTypeIssueAuto-fix?
1ErroruploadJavaScript uploads blockedYes
2WarningconfigMultiple manifest files foundNo

Phase 6 — Offer Auto-Fixes

For each Error finding with autoFixAvailable: true, in order:

🚦 Gate (consent · diagnose-deployment:6.auto-fix): Per-finding consent before applying any auto-fix. Loops once per Error finding with autoFixAvailable: true — each finding gets its own Yes / No / Skip-all AskUserQuestion. The pattern ID surfaces in the prompt. Never batch fixes — three findings = three separate consent prompts (unless the user picks "Skip all" on the first, which short-circuits the loop). The Yes from finding 1 does NOT cover finding 2; each fix has its own blast radius (different files, different settings, different reversibility).

  1. Explain the issue and proposed fix

  2. Ask explicit permission via AskUserQuestion:

    "Issue: {message} Proposed fix: {suggestedFix} Apply this fix? Yes / No / Skip all auto-fixes"

  3. If approved, execute the fix:

    stale-manifest: Delete *-manifest.yml file(s) in .powerpages-site/

    bash
    # Ask which manifest to delete if multiple found, then:
    rm ".powerpages-site/{manifestFile}"

    blocked-js: Update blockedattachments setting

    bash
    # Get current setting first
    pac env list-settings | grep -i blocked
    # Remove .js from the blocked list (preserve other blocked types)
    pac env update-settings --name blockedattachments --value "{updated-value}"

    missing-website-record-id: Retrieve and update record ID

    bash
    pac pages list
    # Parse output, find matching site by name, then update powerpages.config.json

    auth-expired: Guide re-authentication

    bash
    pac auth create --environment "{envUrl}"
    az login

    empty-build: Run build

    bash
    npm run build
  4. After each fix, re-run the relevant check to verify it resolved the issue. Update finding status to "Fixed" or "Manual required".

Key Constraint: Never apply any fix without explicit user permission. Each fix requires a separate confirmation.

Phase 7 — Present Findings Summary

Display a final summary table of all findings:

#SeverityTypeIssueStatus
1ErroruploadJS uploads blockedFixed
2ErrorconfigMissing websiteRecordIdManual required
3WarningconfigMultiple manifest filesInformational

Status values:

  • Fixed: Auto-fix was applied and verified
  • Manual required: No auto-fix available — show manual steps
  • Skipped: User declined the fix
  • Informational: Warning/Info, no action needed

If all errors are resolved: suggest retrying deployment with /power-pages:deploy-site.

If manual steps remain: list them explicitly with commands or links.

Record Skill Usage

Reference: ${PLUGIN_ROOT}/references/skill-tracking-reference.md

Follow the skill tracking instructions in the reference to record this skill's usage. Use --skillName "DiagnoseDeployment".

Key Decision Points (Wait for User)

  1. Phase 6: Each individual auto-fix requires explicit confirmation before applying
  2. Phase 6: If user says "Skip all auto-fixes", stop offering fixes and go to summary

Error Handling

  • If pac pages upload-code-site produces no output: report "No upload errors detected in current state"
  • If Azure CLI token unavailable: skip Phase 4, note in summary
  • If parse-deployment-errors.js returns no findings: report "No known error patterns detected" and show raw output for manual review

Progress Tracking Table

Task subjectactiveFormDescription
Verify prerequisites and locate projectVerifying prerequisitesCheck PAC CLI, Azure CLI, locate project root and powerpages.config.json
Collect deployment artifactsCollecting deployment artifactsRead config, list manifests, check build output, check solution manifest
Surface upload errorsSurfacing upload errorsRe-run pac pages upload-code-site in capture mode, parse stdout/stderr
Query solution import statusQuerying solution import statusCheck recent failed async operations and import jobs in Dataverse
Diagnose and categorize findingsDiagnosing findingsPattern-match all errors against deployment-error-catalog, assign severity
Offer auto-fixesApplying auto-fixesFor each fixable error, ask permission and execute fix, verify result
Present findings summaryPresenting summaryShow all findings table with severity and fix status, list manual steps

Frequently asked questions

What does the Diagnose Deployment AI skill do?

Surfaces PAC CLI upload errors and Dataverse async operation errors, pattern-matches against a known failure catalog, and optionally auto-fixes identified issues. Use when asked to: "diagnose deployment", "debug deployment", "deployment failed", "show deployment errors", "fix deployment issues", "show upload logs", "why did my deploy fail", or "troubleshoot upload".

Why use Diagnose Deployment on TypingMind?

Because you install it once and use it with any model. Diagnose Deployment 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 Diagnose Deployment in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/power-platform-skills/tree/main/plugins/power-pages/skills/diagnose-deployment. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Diagnose Deployment?

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 Diagnose Deployment?

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

Is the Diagnose Deployment AI skill free?

Yes. It is published on GitHub by microsoft 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇