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Product Discovery · majiayu000 | DecimalAI

researchby majiayu000

Product Discovery

majiayu000/product-discovery

Source majiayu000/spellbook ↗License MIT

Product discovery and market research expert.

SkillScore86Maintained

Automatic

Product Management pack

Last verified 8/24/2026

What it changes

Passed 19 of 22 test cases with the skill, and 13 of 22 without it.

Without skill59%

With skill86%

Checks it passed that the model alone missed

Rejects segment sample sizes below 5 users per segment.
Incorporates cost of delay, dependencies, and alternative solutions.
Categorizes low value and high effort opportunities as items to avoid.

and 6 more in the full report

6 fixed13 passed either way3 still failing0 broke

Pass-rate lift: +27 pp
Tokens: +95%
Agent turns: 0%
Response time: -7%

Model gemini-3.6-flashMeasured 8/24/2026v119 of 22 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/majiayu000-product-discovery/SKILL.md https://app.decimal.ai/s/majiayu000-product-discovery/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add majiayu000-product-discovery, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/majiayu000-product-discovery/ and pins it in .decimal/skills.lock

decimalai skills add majiayu000-product-discovery

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/majiayu000-product-discovery/SKILL.md https://app.decimal.ai/s/majiayu000-product-discovery/SKILL.md

Raw file: /s/majiayu000-product-discovery/SKILL.md ↗ · machine-readable summary at /s/majiayu000-product-discovery.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 6

Prompt

Our head of sales insists that we need to immediately build an automated PDF exporter for our analytics platform because two prospective clients asked for it. I need to push back constructively and establish a proper discovery framework. Can you help me reframe this feature proposal into a structured problem-and-outcome format, draft an interview plan template showing segment sample sizes and findings, and list risky assumptions with test criteria?

What was checked, without and with the skill
Checked	Without skill	With skill
Reframes the request into an underlying problem statement and outcome before listing multiple possible solutions.	Passed	Passed
Specifies a minimum sample size of at least 5 interviews for each target segment.	Missed	Passed
Defines falsifiable success criteria containing measurable target numbers for testing risky assumptions.	Passed	Passed

case-01 · gemini-3.6-flash · 8/24/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md455 lines2 files

Product Discovery

Core Principles

Continuous Discovery — Weekly user conversations, not episodic research
Outcome-Driven — Start with outcomes to achieve, not solutions to build
Assumption Testing — Validate risky assumptions before committing resources
Co-Creation — Build with customers, not just for them
Data-Driven — Use evidence over intuition and stakeholder opinions
Problem-First — Deeply understand the problem space before ideating solutions

Hard Rules (Must Follow)

These rules are mandatory. Violating them means the skill is not working correctly.

No Solution-First Thinking

Never start with a solution. Always define the problem and outcome first.

❌ FORBIDDEN:
"We should build a search bar for the product page"
"Let's add AI recommendations"
"Users need a mobile app"

✅ REQUIRED:
"Problem: Users can't find products (40% exit rate on catalog)
Outcome: Reduce exit rate to 20%
Possible solutions:
1. Search bar with filters
2. AI-powered recommendations
3. Better category navigation
4. Visual product browsing"

Evidence-Based Decisions

Never assume user needs without evidence from real user research.

Track record

Benchmark

19 / 22

test cases passed, vs 13 / 22 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

majiayu000 / spellbook

skills/product-discovery/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1Bundled 1 file

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

Product Discovery

Core Principles

Hard Rules (Must Follow)

No Solution-First Thinking

Evidence-Based Decisions

Track record

Benchmark

Adoption

SkillSafety

Source

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