bulk-research

name	bulk-research
description	Research multiple services in parallel using subagents. Each service gets the full research pass — vendor site, pricing, privacy/GDPR, Reddit sentiment, and recent news — written to both existing research fields and the newer structured fields (userSentiment, redditMentions, recentNews). Use when asked to "research all services", "bulk research", "research these services", or need to populate Research tabs for many services at once.
argument-hint	'<name1>, <name2>, ...' or 'all' or 'category <name>' or 'unresearched'

Bulk Research Skill

Research multiple services in parallel by dispatching one subagent per service.

Argument parsing

Argument	Meaning
ProtonMail, Tutanota, Mailbox.org	Research these specific services
all	Research every service in Payload
unresearched	Research services where researchStatus is "not-started"
category Email	Research all services in the Email category
needs-update	Research services where researchStatus is "needs-update"

Process

Step 1: Build the service list

Based on the argument, query Payload to get the list of services to research.

For specific names: Split the comma-separated argument and trim whitespace.

For all:

mcp__payload__findServices: {"limit": 100, "depth": 0}

For unresearched:

mcp__payload__findServices: {"where": "{\"researchStatus\": {\"equals\": \"not-started\"}}", "limit": 100}

For needs-update:

mcp__payload__findServices: {"where": "{\"researchStatus\": {\"equals\": \"needs-update\"}}", "limit": 100}

For category X: First find the category ID, then query services:

mcp__payload__findServices: {"where": "{\"category\": {\"equals\": CATEGORY_ID}}", "limit": 100}

Step 2: Confirm with user

Before dispatching agents, show the user:

• Total number of services to research
• List of service names
• Ask for confirmation to proceed

This prevents accidentally researching 100 services when the user meant 5.

Step 3: Dispatch parallel research agents

Use the Agent tool to launch one subagent per service. All agents run in parallel.

Critical rules for parallel dispatch:

• Each agent gets a complete, self-contained prompt with all context it needs
• Agents do NOT share state or read from each other
• Each agent operates on a different service (no file conflicts)
• Use run_in_background: true for all agents

Agent prompt template (one per service):

You are researching the service "{SERVICE_NAME}" for switch-to.eu.

Use the /research skill to research this service. Here is the full process:

1. Find the service in Payload using mcp__payload__findServices with:
   {"where": "{\"name\": {\"contains\": \"{SERVICE_NAME}\"}}", "limit": 5}

2. Research using `mcp__Payload__jina_read`, `mcp__Payload__jina_search`, and the Reddit MCP (see `_shared/jina.md`):
   - Company basics: website, headquarters, parent company, founded year, employees, open source
   - Pricing: free tier, paid plans, enterprise, pricing page URL
   - Privacy & GDPR: data storage locations, compliance status, DPA, privacy policy URL
   - Security: certifications, breaches, audits
   - Reddit sentiment: search default subreddits (r/privacy, r/europe, r/selfhosted, r/degoogle) for the service; classify posts as positive/negative/mixed/neutral; collect snippets
   - Recent news: Jina Search with time filter, last 12 months, top 10 results by recency

3. Store findings via mcp__payload__updateServices with the service ID.
   Map all fields: gdprCompliance, gdprNotes, privacyPolicyUrl, pricingDetails, pricingUrl,
   headquarters, parentCompany, foundedYear, employeeCount, dataStorageLocations, certifications,
   openSource, sourceCodeUrl, researchNotes (Lexical richText JSON), sourceUrls,
   userSentiment (group with positive/negative/mixed counts + 2-3 sentence summary),
   redditMentions (array of {subreddit, postUrl, postTitle, sentiment, snippet, date}),
   recentNews (array of {source, url, title, date, summary}),
   researchStatus: "complete", lastResearchedAt: today's ISO date.

   Apply merge semantics: don't overwrite non-empty scalar fields with empty values.
   userSentiment / redditMentions / recentNews always replace (time-sensitive).

4. Also update General tab if empty: location, url, freeOption, startingPrice.

Return a brief summary: service name, key findings, any gaps needing follow-up.

Dispatch all agents in a single message with multiple Agent tool calls. Use subagent_type: "general-purpose" and run_in_background: true.

Step 4: Collect results

As agents complete, collect their summaries. When all are done, present a consolidated report:

## Bulk Research Complete

Researched: X/Y services

| Service | Status | Key Finding | Gaps |
|---------|--------|-------------|------|
| ProtonMail | Done | Swiss-based, GDPR compliant | None |
| Tutanota | Done | German-based, open source | Employee count unknown |
| ... | ... | ... | ... |

Failed: [list any that failed with reasons]

Guardrails

• Max parallel agents: 10 at a time. If more than 10 services, batch them in groups of 10 and wait for each batch to complete before starting the next.
• Rate limiting: The MCP server and web searches have rate limits. Batching in groups of 10 helps avoid hitting these.
• Error handling: If an agent fails, note it in the report but don't retry automatically. The user can re-run individual failures with /research.