Customer Research

by anthropicsae1513ea94dcNo license27K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today

Multi-source research on a customer question or topic with source attribution. Use when a customer asks something you need to look up, investigating whether a bug has been reported before, checking what was previously told to a specific account, or gathering background before drafting a response.

FeaturedInstructions onlyResearch & AnalysisCommunication
AI-generated overview

Multi-source research on customer questions, issues, or accounts, producing an attributed brief with confidence levels.

What it does
Guides an agent through researching a customer question, reported issue, account history, or support topic across internal and external source tiers. It produces a structured research brief with a direct answer, confidence rating, key findings by source, context, sources, gaps, and recommended next steps. It also covers escalation guidance, contradiction handling, and optional knowledge-base documentation.
When to use it
Use when a customer asks something that needs looking up, when investigating whether an issue was reported before, when checking what was previously told to a specific account, or when gathering background before drafting a response.
Requirements
Instructions only; no scripts. Works best with connected sources such as knowledge base, cloud storage, CRM, support platform, chat, email, and calendar, and may fall back to web search. No specific packages or credentials are required by the skill itself.

/customer-research

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Multi-source research on a customer question, product topic, or account-related inquiry. Synthesizes findings from all available sources with clear attribution and confidence scoring.

Usage

/customer-research <question or topic>

Workflow

1. Parse the Research Request

Identify what type of research is needed:

  • Customer question: Something a customer has asked that needs an answer (e.g., "Does our product support SSO with Okta?")
  • Issue investigation: Background on a reported problem (e.g., "Has this bug been reported before? What's the known workaround?")
  • Account context: History with a specific customer (e.g., "What did we tell Acme Corp last time they asked about this?")
  • Topic research: General topic relevant to support work (e.g., "Best practices for webhook retry logic")

Before searching, clarify what you're actually trying to find:

  • Is this a factual question with a definitive answer?
  • Is this a contextual question requiring multiple perspectives?
  • Is this an exploratory question where the scope is still being defined?
  • Who is the audience for the answer (internal team, customer, leadership)?

2. Search Available Sources

Search systematically through the source tiers below, adapting to what is connected. Don't stop at the first result — cross-reference across sources.

Tier 1 — Official Internal Sources (highest confidence):

  • ~~knowledge base (if connected): product docs, runbooks, FAQs, policy documents
  • ~~cloud storage: internal documents, specs, guides, past research
  • Product roadmap (internal-facing): feature timelines, priorities

Tier 2 — Organizational Context:

  • ~~CRM notes: account notes, activity history, previous answers, opportunity details
  • ~~support platform (if connected): previous resolutions, known issues, workarounds
  • Meeting notes: previous discussions, decisions, commitments

Tier 3 — Team Communications:

  • ~~chat: search for the topic in relevant channels; check if teammates have discussed or answered this before
  • ~~email: search for previous correspondence on this topic
  • Calendar notes: meeting agendas and post-meeting notes

Tier 4 — External Sources:

  • Web search: official documentation, blog posts, community forums
  • Public knowledge bases, help centers, release notes
  • Third-party documentation: integration partners, complementary tools

Tier 5 — Inferred or Analogical (use when direct sources don't yield answers):

  • Similar situations: how similar questions were handled before
  • Analogous customers: what worked for comparable accounts
  • General best practices: industry standards and norms

3. Synthesize Findings

Compile results into a structured research brief:

## Research: [Question/Topic]
### Answer[Clear, direct answer to the question — lead with the bottom line]
**Confidence:** [High / Medium / Low][Explain what drives the confidence level]
### Key Findings
**From [Source 1]:**- [Finding with specific detail]- [Finding with specific detail]
**From [Source 2]:**- [Finding with specific detail]
### Context & Nuance[Any caveats, edge cases, or additional context that matters]
### Sources1. [Source name/link] — [what it contributed]2. [Source name/link] — [what it contributed]3. [Source name/link] — [what it contributed]
### Gaps & Unknowns- [What couldn't be confirmed]- [What might need verification from a subject matter expert]
### Recommended Next Steps- [Action if the answer needs to go to a customer]- [Action if further research is needed]- [Who to consult for verification if needed]

4. Handle Insufficient Sources

If no connected sources yield results:

  • Perform web research on the topic
  • Ask the user for internal context:
    • "I couldn't find this in connected sources. Do you have internal docs or knowledge base articles about this?"
    • "Has your team discussed this topic before? Any ~~chat channels I should check?"
    • "Is there a subject matter expert who would know the answer?"
  • Be transparent about limitations:
    • "This answer is based on web research only — please verify against your internal documentation before sharing with the customer."
    • "I found a possible answer but couldn't confirm it from an authoritative internal source."

5. Customer-Facing Considerations

If the research is to answer a customer question:

  • Flag if the answer involves product roadmap, pricing, legal, or security topics that may need review
  • Note if the answer differs from what may have been communicated previously
  • Suggest appropriate caveats for the customer-facing response
  • Offer to draft the customer response: "Want me to draft a response to the customer based on these findings?"

6. Knowledge Capture

After research is complete, suggest capturing the knowledge:

  • "Should I save these findings to your knowledge base for future reference?"
  • "Want me to create a FAQ entry based on this research?"
  • "This might be worth documenting — should I draft a runbook entry?"

This helps build institutional knowledge and reduces duplicate research effort across the team.


Source Prioritization and Confidence

Confidence by Source Tier

TierSource TypeConfidenceNotes
1Official internal docs, KB, policiesHighTrust unless clearly outdated — check dates
2CRM, support tickets, meeting notesMedium-HighMay be subjective or incomplete
3Chat, email, calendar notesMediumInformal, may be out of context or speculative
4Web, forums, third-party docsLow-MediumMay not reflect your specific situation
5Inference, analogies, best practicesLowClearly flag as inference, not fact

Confidence Levels

Always assign and communicate a confidence level:

High Confidence:

  • Answer confirmed by official documentation or authoritative source
  • Multiple sources corroborate the same answer
  • Information is current (verified within a reasonable timeframe)
  • "I'm confident this is accurate based on [source]."

Medium Confidence:

  • Answer found in informal sources (chat, email) but not official docs
  • Single source without corroboration
  • Information may be slightly outdated but likely still valid
  • "Based on [source], this appears to be the case, but I'd recommend confirming with [team/person]."

Low Confidence:

  • Answer is inferred from related information
  • Sources are outdated or potentially unreliable
  • Contradictory information found across sources
  • "I wasn't able to find a definitive answer. Based on [context], my best assessment is [answer], but this should be verified before sharing with the customer."

Unable to Determine:

  • No relevant information found in any source
  • Question requires specialized knowledge not available in sources
  • "I couldn't find information about this. I recommend reaching out to [suggested expert/team] for a definitive answer."

Handling Contradictions

When sources disagree:

  1. Note the contradiction explicitly
  2. Identify which source is more authoritative or more recent
  3. Present both perspectives with context
  4. Recommend how to resolve the discrepancy
  5. If going to a customer: use the most conservative/cautious answer until resolved

When to Escalate vs. Answer Directly

Answer Directly When:

  • Official documentation clearly addresses the question
  • Multiple reliable sources corroborate the answer
  • The question is factual and non-sensitive
  • The answer doesn't involve commitments, timelines, or pricing
  • You've answered similar questions before with confirmed accuracy

Escalate or Verify When:

  • The answer involves product roadmap commitments or timelines
  • Pricing, legal terms, or contract-specific questions
  • Security, compliance, or data handling questions
  • The answer could set a precedent or create expectations
  • You found contradictory information in sources
  • The question involves a specific customer's custom configuration
  • The answer requires specialized expertise you don't have
  • The customer is at risk and the wrong answer could exacerbate the situation

Escalation Path:

  1. Subject matter expert: For technical or domain-specific questions
  2. Product team: For roadmap, feature, or capability questions
  3. Legal/compliance: For terms, privacy, security, or regulatory questions
  4. Billing/finance: For pricing, invoice, or payment-related questions
  5. Engineering: For custom configurations, bugs, or technical root causes
  6. Leadership: For strategic decisions, exceptions, or high-stakes situations

Research Documentation for Team Knowledge Base

After completing research, capture the knowledge for future use.

When to Document:

  • Question has come up before or likely will again
  • Research took significant effort to compile
  • Answer required synthesizing multiple sources
  • Answer corrects a common misunderstanding
  • Answer involves nuance that's easy to get wrong

Documentation Format:

## [Question/Topic]
**Last Verified:** [date]**Confidence:** [level]
### Answer[Clear, direct answer]
### Details[Supporting detail, context, and nuance]
### Sources[Where this information came from]
### Related Questions[Other questions this might help answer]
### Review Notes[When to re-verify, what might change this answer]

Knowledge Base Hygiene:

  • Date-stamp all entries
  • Flag entries that reference specific product versions or features
  • Review and update entries quarterly
  • Archive entries that are no longer relevant
  • Tag entries for searchability (by topic, product area, customer segment)

Source and attribution

Source:anthropics/knowledge-work-pluginsincustomer-support/skills/customer-researchat commitae1513e

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

Report or request removal

More from anthropics/knowledge-work-plugins

Ticket Deflector

anthropics

Featured

Reads a forwarded customer email or ticket, pulls order and refund status from a payments connector (PayPal, Square, or Stripe) or Shopify, account history from the CRM, and open tickets from a support desk (Zoho Desk), drafts a tone-matched reply in the owner's writing voice, and can issue a refund through the payments connector with explicit owner approval. With Shopify connected it also runs a proactive order-triage mode that surfaces orders needing attention — unfulfilled past the promised window, payment problems, pending refunds, stuck shipments — and drafts the next action for each before the customer has to ask. Use when the user says "draft a response," "answer this customer," "where's my order," "I want a refund," "check my orders," or "anything about to blow up."

Awaiting classification27Kupdated today

Tax Season Organizer

anthropics

Featured

Prepares tax-season materials for the owner's accountant, not tax advice. US federal tax; a non-US business gets its closed-books packet instead. Two modes: (1) quarterly estimated tax from YTD net income in the ledger (MYOB, NetSuite, QuickBooks, Xero, or Zoho Books); (2) year-end 1099 prep, scanning the ledger, PayPal, and Stripe for contractors paid over USD 600 into a 1099-NEC list with missing W-9 flags. Any tax request routes first to /tax-prep, which confirms the books are closed and reconciled before running this skill. Use this skill directly only when the owner says the period's books are already closed: "books are closed, now do the 1099s," "run the quarterly estimate off the closed numbers," or "just the contractor W-9 list."

Awaiting classification27Kupdated today

Tax Prep

anthropics

Featured

Prepares tax materials from closed books: a quarterly estimated payment breakdown or a year-end 1099-NEC list and accountant packet.

Business & Finance27Kupdated today

Smb Onboard

anthropics

Featured

Guides a small-business owner through first-time setup: connecting tools, running a value-proof recipe, capturing business context, and setting a weekly…

Productivity & Workflow27Kupdated today

Smb Router

anthropics

Featured

Routes a small-business owner's request to the right plugin skill or command and explains what is available.

Productivity & Workflow27Kupdated today

Month End Prep

anthropics

Featured

Reconciles the accounting ledger (MYOB, NetSuite, QuickBooks, Xero, or Zoho Books) against PayPal, Shopify, Square, and Stripe settlements, flags transactions that need attention, suspicious duplicates, and missing receipts, then writes a plain-English P&L narrative and exports a close packet (xlsx + one-page PDF). This is the first link of the /close-month command; a request to close the month or the books routes there, and the command runs this skill before refreshing the forecast and distributing the packet. Use this skill directly only when the owner wants the reconciliation alone, with no forecast refresh and no distribution: "just reconcile, no packet," "what's missing from the books," "flag the duplicates and missing receipts," or "write the P&L narrative for this month."

Awaiting classification27Kupdated today