How do I install the Feature Investment Advisor skill?

Run npx skillmds@latest add nandanosql/feature-investment-advisor in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Feature Investment Advisor safe to use?

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Which AI agents work with Feature Investment Advisor?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Feature Investment Advisor free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Feature Investment Advisor?

nandanosql (@nandanosql) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Feature Investment Advisor by nandanosql

Name: Feature Investment Advisor
Author: nandanosql

File contents

Purpose

Evaluate whether to invest more, iterate on, or sunset existing features — using adoption data, engineering costs, and strategic alignment to make rational feature portfolio decisions.

Application

Turn 1: Feature Context

Agent asks: "Which feature are you evaluating? Tell me about it."

Feature name and purpose
When it launched
Target user segment

Turn 2: Adoption Data

Agent asks: "What do the numbers say?"

% of users who use this feature (adoption)
Frequency of use (daily/weekly/monthly)
Impact on retention (do users who use it retain better?)
Revenue attribution (does it drive upgrades?)
Support load (does it generate tickets?)

Turn 3: Investment Assessment

Agent asks: "What does it cost to maintain and improve?"

Engineering time spent on maintenance
Bug volume
Requested improvements backlog
Competitive necessity (do competitors have it?)

Output: Investment Recommendation

# Feature Investment Assessment: [Feature Name]

## Scorecard
| Dimension | Score (1-5) | Evidence |
|-----------|-----------|---------|
| Adoption | [#] | [% users, frequency] |
| Retention Impact | [#] | [Cohort comparison] |
| Revenue Impact | [#] | [Upgrade correlation] |
| Strategic Alignment | [#] | [Fits current strategy?] |
| Maintenance Cost | [#] | [Eng hours/sprint] |
| **Total** | **[#/25]** | |

## Recommendation: [Invest / Iterate / Maintain / Sunset]

### If Invest (Score >18)
- [ ] Allocate [X] sprints for improvement
- [ ] Target metric: [Increase adoption from X% to Y%]

### If Iterate (Score 12-18)
- [ ] Run [specific experiment] to test improvement
- [ ] Revisit in [X weeks]

### If Maintain (Score 8-12)
- [ ] Bug fixes only, no new investment
- [ ] Monitor for decline

### If Sunset (Score <8)
- [ ] Plan EOL communication
- [ ] Migrate users to alternative
- [ ] Use `skills/launch/eol-message/SKILL.md`

References

Related Skills

skills/analytics/funnel-analysis/SKILL.md — Usage data
skills/growth/retention-deep-dive/SKILL.md — Retention impact
skills/launch/eol-message/SKILL.md — If sunsetted

Skill type: Interactive Domain: Growth & Optimization

---name: feature-investment-advisordescription: Evaluate whether to invest in, iterate on, or sunset existing features — using adoption data, effort costs, and strategic alignment to make rational investment decisions.---## PurposeEvaluate whether to **invest more, iterate on, or sunset** existing features — using adoption data, engineering costs, and strategic alignment to make rational feature portfolio decisions.---## Application### Turn 1: Feature Context**Agent asks:** "Which feature are you evaluating? Tell me about it."- Feature name and purpose- When it launched- Target user segment### Turn 2: Adoption Data**Agent asks:** "What do the numbers say?"- % of users who use this feature (adoption)- Frequency of use (daily/weekly/monthly)- Impact on retention (do users who use it retain better?)- Revenue attribution (does it drive upgrades?)- Support load (does it generate tickets?)### Turn 3: Investment Assessment**Agent asks:** "What does it cost to maintain and improve?"- Engineering time spent on maintenance- Bug volume- Requested improvements backlog- Competitive necessity (do competitors have it?)### Output: Investment Recommendation```markdown# Feature Investment Assessment: [Feature Name]## Scorecard| Dimension | Score (1-5) | Evidence ||-----------|-----------|---------|| Adoption | [#] | [% users, frequency] || Retention Impact | [#] | [Cohort comparison] || Revenue Impact | [#] | [Upgrade correlation] || Strategic Alignment | [#] | [Fits current strategy?] || Maintenance Cost | [#] | [Eng hours/sprint] || **Total** | **[#/25]** | |## Recommendation: [Invest / Iterate / Maintain / Sunset]### If Invest (Score >18)- [ ] Allocate [X] sprints for improvement- [ ] Target metric: [Increase adoption from X% to Y%]### If Iterate (Score 12-18)- [ ] Run [specific experiment] to test improvement- [ ] Revisit in [X weeks]### If Maintain (Score 8-12)- [ ] Bug fixes only, no new investment- [ ] Monitor for decline### If Sunset (Score <8)- [ ] Plan EOL communication- [ ] Migrate users to alternative- [ ] Use `skills/launch/eol-message/SKILL.md````---## References### Related Skills- `skills/analytics/funnel-analysis/SKILL.md` — Usage data- `skills/growth/retention-deep-dive/SKILL.md` — Retention impact- `skills/launch/eol-message/SKILL.md` — If sunsetted---**Skill type:** Interactive**Domain:** Growth & Optimization

Frequently asked questions

Feature Investment Advisor