Files
marketingskills/skills/customer-research/evals/evals.json
Corey Haines cc1a9c106b feat: add Nitrosend integration for AI-native email sequencing (#202)
* feat: add customer-research skill (#186)

* feat: add customer-research skill (#185)

Adds a new skill for conducting and synthesizing customer research —
covering analysis of existing assets (transcripts, surveys, support
tickets, NPS) and digital watering hole research (Reddit, G2, forums,
communities, review sites). Includes persona generation framework,
JTBD extraction, VOC quote banking, and competitive intel from reviews.

Also adds a detailed source-guides reference with per-platform playbooks
(Reddit operators, G2 review tiers, LinkedIn job posting mining, etc.)
and 10 evals covering the main trigger scenarios.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: address Codex review of customer-research skill

- Fix evals.json schema to match repo convention (skill_name wrapper,
  integer IDs, expected_output, files fields)
- Add product-marketing-context.md assertion to all evals
- Add 2 new evals: B2C drop-off scenario and zero-research bootstrap
- Collapse 'Where to Look' in SKILL.md to a decision table; detail
  lives in source-guides.md
- Add Research Quality Guardrails section (confidence labels,
  recency window, sample bias, minimum viable sample)
- Add Related Skills section cross-linking 7 downstream skills
- Expand source-guides.md with full B2C section (app stores,
  TikTok/Instagram, consumer Reddit, Discord)
- Add Source Reliability and Confidence Scoring reference guide

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: correct alphabetical ordering of customer-research in manifest and README

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* docs: add customer-research to skills relationship diagram

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* docs: move customer-research into Strategy column in diagram

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

* feat: Resend CLI docs + Firehose integration (#188)

* feat: add Resend CLI docs and Firehose integration

- resend.md: update CLI availability (now official), add CLI install,
  setup, and common commands section
- firehose.md: new integration guide for real-time web content streaming
  API — query syntax, stream setup, marketing use cases (brand monitoring,
  competitive intel, lead triggers, PR/link building)
- REGISTRY.md: add firehose under Competitive Intelligence

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* docs: document Claude Code dynamic content injection pattern

Add Claude Code-specific enhancement section to AGENTS.md explaining
the !`command` syntax for injecting shell output into skills at
invocation time. Marked as Claude Code-only to preserve cross-agent
compatibility of SKILL.md files.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Revert "docs: document Claude Code dynamic content injection pattern"

This reverts commit 8e1ce7b363.

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

* docs: document Claude Code dynamic content injection pattern (#189)

Add Claude Code-specific enhancement section to AGENTS.md explaining
the !`command` syntax for injecting shell output into skills at
invocation time. Marked as Claude Code-only to preserve cross-agent
compatibility of SKILL.md files.

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

* feat: add Introw PRM as partner ecosystem integration (#193)

Great contribution — clean integration guide with solid MCP tool coverage, and the cross-references into referral-program, revops, launch-strategy, and sales-enablement are well-placed. Thanks!

* feat: add Nitrosend integration for AI-native email sequencing

Adds Nitrosend as a tool option for teams building email sequences via
AI agents — no dashboard required, full MCP control.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Tibo <72124096+CoopahG@users.noreply.github.com>
2026-03-27 23:32:13 -07:00

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{
"skill_name": "customer-research",
"evals": [
{
"id": 1,
"prompt": "I have 20 customer interview transcripts. Help me analyze them.",
"expected_output": "Should check for product-marketing-context.md first. Should ask about the goal before analyzing (improve messaging, build personas, find product gaps, etc.). Should apply the extraction framework: jobs to be done, pain points, trigger events, desired outcomes, language/vocabulary, alternatives considered. Should recommend clustering by theme, frequency + intensity scoring, and identifying money quotes. Should ask which deliverable is needed.",
"assertions": [
"Checks for product-marketing-context.md",
"Asks about the goal before diving in (improve messaging, build personas, find gaps, etc.)",
"Mentions extracting jobs to be done, pain points, and desired outcomes",
"Suggests organizing quotes by theme",
"References frequency and intensity scoring",
"Asks which deliverable is needed"
],
"files": []
},
{
"id": 2,
"prompt": "I want to do ICP research but I don't have any customer interviews yet.",
"expected_output": "Should check for product-marketing-context.md first. Should recommend digital watering hole research as a starting point. Should mention Reddit, G2, Capterra, forums, or niche communities as sources. Should offer to plan a research approach and explain what to extract from online sources. Should note this is Mode 2 and ask what product/category to research.",
"assertions": [
"Checks for product-marketing-context.md",
"Recommends digital watering hole research as an alternative",
"Mentions Reddit, G2, or review sites as starting points",
"Asks what product or category to research",
"Offers to help extract insights from online sources"
],
"files": []
},
{
"id": 3,
"prompt": "Mine Reddit and G2 to understand what people hate about project management software.",
"expected_output": "Should check for product-marketing-context.md first. Should identify relevant subreddits (r/projectmanagement, r/productivity, r/agile) and search strategies. Should recommend reading 3-star and 1-star G2 reviews and competitor 4-star reviews. Should plan to extract verbatim quotes, pain themes, and switching triggers. Should apply the extraction table (source, quote, context, sentiment, theme tag, profile signals).",
"assertions": [
"Checks for product-marketing-context.md",
"Identifies relevant subreddits or search strategies for project management",
"Suggests reading 3-star and 1-star G2 reviews",
"Recommends competitor 4-star reviews for buried complaints",
"Plans to extract verbatim quotes and pain themes",
"Mentions what to look for: complaints, workarounds, switching triggers"
],
"files": []
},
{
"id": 4,
"prompt": "Build me a customer persona for a marketing manager at a B2B SaaS company.",
"expected_output": "Should check for product-marketing-context.md first. Should ask if there is existing research to build from before generating a persona. Should warn against inventing details without data. Should use the persona structure: profile, primary JTBD, trigger events, top pains, desired outcomes, objections, alternatives, key vocabulary, how to reach them. Should note that personas should be built from at least 5-10 data points.",
"assertions": [
"Checks for product-marketing-context.md",
"Asks if there is existing research to build from before inventing details",
"Warns against creating personas without data",
"Includes jobs to be done, pains, triggers, and desired outcomes in persona structure",
"Mentions the need to capture actual customer vocabulary",
"Notes minimum data threshold (5-10 data points)"
],
"files": []
},
{
"id": 5,
"prompt": "I have 6 months of customer support tickets. What insights can I pull from them?",
"expected_output": "Should check for product-marketing-context.md first. Should recommend categorizing tickets before analyzing (bugs vs. confusion vs. feature requests vs. expectation mismatches). Should warn against treating all tickets as equal signal. Should suggest extracting recurring language, patterns, and 'I wish it could…' phrases. Should ask about the goal — product improvement, messaging, reducing support load, or something else.",
"assertions": [
"Checks for product-marketing-context.md",
"Recommends categorizing tickets before analyzing (bugs vs confusion vs feature requests)",
"Warns against treating all tickets as equal signal",
"Mentions extracting recurring language and patterns",
"Asks about the goal — product improvement, messaging, or something else"
],
"files": []
},
{
"id": 6,
"prompt": "What are customers saying about my competitors on review sites?",
"expected_output": "Should check for product-marketing-context.md first. Should ask which competitors to research. Should recommend G2 and Capterra as primary sources. Should specifically call out reading competitor 4-star reviews for buried complaints. Should describe what to extract: what they love (battlecard intel), what frustrates them (opportunities), unmet needs. Should use the review mining template.",
"assertions": [
"Checks for product-marketing-context.md",
"Recommends reading competitor 4-star reviews specifically for buried complaints",
"Mentions G2 or Capterra as sources",
"Describes what to extract: what they love, what frustrates them, unmet needs",
"Frames as competitive intelligence input"
],
"files": []
},
{
"id": 7,
"prompt": "Help me do voice of customer research for a new SaaS in the HR space.",
"expected_output": "Should check for product-marketing-context.md first. Should ask about the specific ICP segment within HR (recruiter, HR generalist, CHRO, etc.). Should suggest relevant digital watering holes: r/humanresources, r/recruiting, HR Slack communities, G2 HR category, LinkedIn. Should plan to extract verbatim language for copy use. Should offer to produce a VOC quote bank as a deliverable.",
"assertions": [
"Checks for product-marketing-context.md",
"Asks about target ICP segment within HR",
"Suggests relevant digital watering holes (subreddits, G2 categories, communities)",
"Plans to extract verbatim language for copy use",
"Mentions organizing findings into a VOC quote bank"
],
"files": []
},
{
"id": 8,
"prompt": "I want to understand why customers churn. I have exit survey results.",
"expected_output": "Should check for product-marketing-context.md first. Should recommend segmenting churn reasons before analyzing — do not average across different causes. Should suggest pairing open-ended responses with quantitative data. Should ask if win/loss interview data or support tickets are also available. Should apply confidence labels (high/med/low) based on sample size and source consistency.",
"assertions": [
"Checks for product-marketing-context.md",
"Recommends segmenting churn reasons before analyzing",
"Warns against averaging across different churn causes",
"Suggests pairing open-ended responses with quantitative data",
"Asks if win/loss interview data is also available"
],
"files": []
},
{
"id": 9,
"prompt": "Find the digital watering holes where DevOps engineers talk shop.",
"expected_output": "Should check for product-marketing-context.md first. Should identify specific relevant communities: r/devops, r/sysadmin, Hacker News, DevOps-focused Discord/Slack groups, LinkedIn, Stack Overflow. Should suggest what to search for in those communities. Should describe what signal to extract from each source type and reference source-guides.md for detailed playbooks.",
"assertions": [
"Checks for product-marketing-context.md",
"Mentions specific relevant communities (r/devops, Hacker News, LinkedIn, Discord)",
"Suggests what to search for in those communities",
"Describes what signal to extract from each source type"
],
"files": []
},
{
"id": 10,
"prompt": "Turn my customer research into messaging I can use on my homepage.",
"expected_output": "Should check for product-marketing-context.md first. Should extract VOC language and top themes before moving to copy. Should identify the highest-signal quotes and language patterns. Should produce a VOC summary or quote bank, then hand off to the copywriting skill for the actual copy writing step rather than writing homepage copy directly.",
"assertions": [
"Checks for product-marketing-context.md",
"Extracts the VOC language and themes first before jumping to copy",
"Identifies the highest-signal quotes for messaging",
"References the copywriting skill for the actual copy writing step"
],
"files": []
},
{
"id": 11,
"prompt": "I run a mobile fitness app and want to understand why users drop off after week 2.",
"expected_output": "Should check for product-marketing-context.md first. Should recognize this as a B2C research scenario. Should suggest B2C-appropriate sources: app store reviews (1-3 star), Reddit fitness communities, YouTube comment sections on fitness apps, TikTok/Instagram comments. Should also recommend in-app surveys and analyzing support tickets/reviews. Should frame around activation and habit formation research.",
"assertions": [
"Checks for product-marketing-context.md",
"Recognizes this as a B2C research scenario",
"Suggests app store reviews as a primary source",
"Mentions Reddit or community sources relevant to fitness/consumer apps",
"Frames around understanding drop-off triggers and desired outcomes"
],
"files": []
},
{
"id": 12,
"prompt": "I have no existing research and don't know who my best customers are yet.",
"expected_output": "Should check for product-marketing-context.md first. Should treat this as a bootstrap research scenario. Should recommend starting with hypothesis formation before gathering data. Should suggest a minimum viable research plan: 5-10 customer interviews + digital watering hole scan. Should provide interview recruiting tips and what questions to ask. Should warn against building personas before collecting any data.",
"assertions": [
"Checks for product-marketing-context.md",
"Recognizes this as a zero-research bootstrap scenario",
"Recommends forming hypotheses before gathering data",
"Suggests a minimum viable research plan (interviews + online sources)",
"Warns against building personas without any data"
],
"files": []
}
]
}