Hire an AI firmware update recovery test planner

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A revision-specific compatibility and recovery matrix.
• A fault-rehearsal plan and evidence register.
• A canary proposal with agreed thresholds, owners and open rollout decisions.

How it does the job well

• Read the existing code, its conventions and its tests before changing anything. Match the project's patterns.
• Make the smallest change that fully solves the request. Keep unrelated refactors out.
• Reproduce a bug before fixing it, and add a test that fails without the fix.
• Treat input from users, files and networks as untrusted. Validate it at the boundary.

Mistakes it avoids

• Claiming code works without running it or its tests.
• Inventing APIs, package versions or settings instead of checking the installed ones.
• Changing behaviour outside the request, such as reformatting whole files or renaming public interfaces.

What a good result looks like

An example, not your task: You need a revision-specific compatibility and recovery matrix.

• Compatibility and recovery matrix. Each hardware revision with its update path, recovery access and open questions.
• Test matrix. Failure cases such as cut downloads and bad images, each with expected safe state and evidence needed.
• Evidence register. PASS, FAIL, NOT_RUN or BLOCKED for each case, linked to real logs.
• Canary proposal. Which devices go first, health windows, stop conditions, owners and open decisions.

How the work is checked

• The changed files build, and the relevant tests and linters pass. The commands and results are shown.
• Each change is explained in one line with its reason, and risky areas are named.
• Any check that could not run is reported as NOT_RUN with what it needs.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

Capabilities

• Bind the hardware and update revision. Compatibility/recovery matrix and unresolved prerequisites.
• Specify the recovery rehearsal. Test matrix with case ID, revision, expected transition, recovery path and evidence needed.
• Run authorized lab checks or assess supplied evidence. Revision-bound PASS/FAIL/NOT_RUN/BLOCKED register with actual logs/artifacts.
• Prepare a hardware-diverse canary proposal. Canary plan, acceptance/stop conditions, owners and unresolved decision list.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id firmware-update-recovery-rehearsal only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/firmware-update-recovery-rehearsal/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• Hardware/bootloader revisions, partition map and current/target firmware revisions.
• Update manifest and verification/boot-confirm design, without secret values.
• Connectivity, health windows, physical recovery path and available lab evidence.

Functions and deliverables

• Firmware update recovery test planner: Share your device and update design. Plan failure tests, review recovery evidence and prepare a gated rollout proposal.
  • A revision-specific compatibility and recovery matrix.
  • A fault-rehearsal plan and evidence register.
  • A canary proposal with agreed thresholds, owners and open rollout decisions.
  Source: Michael Sitarzewski and Agency Agents contributors.
• Lab and device standards evidence planner: Name an ISO standard and share records. Get a draft evidence list for expert review.
  • An evidence gap list
  • Records mapped to process areas
  • A list of blockers and open decisions
  • A draft marked for human review
  Source: K-Dense.
• Service rollout and rollback planner: Plan a safe service rollout and rollback. Share your release or infrastructure change and get preflight checks, stages, health signals and a rollback plan.
  • A summary with the risk level and rollback time
  • Preflight checks with a go or no-go list
  • Rollout steps with commands and a check after each
  • Health signals to watch over the first 15 minutes and beyond
  • A rollback plan with clear triggers
  • A communication plan and a list of contacts
  Source: GitHub Copilot community.
• Expo update health checker: Name an Expo update or channel. Get aggregate launch-failure, adoption and payload metrics through the signed-in EAS tools.
  • Crash rate and failed launch counts for each platform
  • Launch and unique user counts
  • How many users run the embedded build and how many run updates
  • The most popular updates on a channel
  • Average update size
  Source: sickn33.
• AI project context organiser: Share your project and next task. Get a short rules file, a focused file list and a clear handoff for later sessions.
  • A ready rules file for your project
  • A list of which files to load for each task
  • Rules for when to reset or trim the session
  • A checklist for spotting drifting answers
  Source: Addy Osmani.

Tasks you can use it for

• You need a revision-specific compatibility and recovery matrix.

Limits to check before starting

• You want a general review of embedded code: use the Embedded firmware engineer.
• You want day-to-day help running a fleet of connected devices: use the IoT fleet rollout planner.
• You have no lab and no past test records. It still plans the tests, but it cannot call an update safe to roll out.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the workflow and give the complete files to your AI.
• Ask it to read the governing instructions and workflow-state.json, then start with the first stage.
• Supply missing evidence at the checkpoint; keep later stages pending until their inputs exist.
• Review actual results, open items and any proposed external action.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/firmware-update-recovery-rehearsal for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.