PM Feature Investment Advisor

SkillDev tools

Evaluate whether a feature deserves investment using revenue linkage, cost structure, strategic value, and risk.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the PM Feature Investment Advisor skill

What this skill tells your AI

The instructions your AI receives, as published by contextgo/contextgo in src/process/resources/skills/pm-workbench-pack/skills/pm-feature-investment-advisor/SKILL.md and read by ahel’s review.

Use this skill when prioritization needs a financial and strategic investment lens, not just a feature ranking score.

What this skill asks

Should we invest in this feature now, later, or not at all?

That means looking at:

  • revenue connection
  • retention or expansion effect
  • one-time build cost
  • ongoing operating cost
  • strategic value
  • downside risk

Use when

  • the initiative is expensive enough to deserve financial scrutiny
  • leadership wants an investment case, not just a score
  • there is a monetization, retention, or enterprise revenue angle
  • a platform or AI feature has meaningful ongoing cost

Do not use when

  • the item is tiny and cheap
  • the work is clear table stakes and must exist regardless of ROI
  • discovery is still too weak to estimate value credibly

Anti-patterns

  • treating top-line revenue as the only value signal
  • ignoring COGS and support overhead
  • confusing strategic necessity with proven ROI
  • building an ROI model from invented adoption numbers and then treating it as fact

Evaluation model

1. Identify the value path

Classify the feature's main value mechanism:

  • direct monetization
  • better conversion
  • retention improvement
  • expansion enablement
  • strategic / enabling investment

The user may mention several. Choose the primary one and note the rest as secondary effects.

2. Estimate the cost structure

Capture:

  • one-time build effort
  • rollout and enablement effort
  • ongoing infra or vendor cost
  • support or operational overhead

If cost is uncertain, present ranges rather than a fake point estimate.

3. Estimate the impact range

Use conservative, base, and upside scenarios when possible.

Examples:

  • adoption rate for a paid add-on
  • churn reduction range for a retention feature
  • pipeline or deal unlock rate for enterprise asks
  • activation lift for onboarding work

4. Add the strategic overlay

A financially weak feature may still make sense if it:

  • unlocks future platform capability
  • protects a critical segment
  • closes a severe compliance or security gap
  • removes a blocker for a larger roadmap move

Make this explicit. Do not smuggle it into the math.

5. Make the decision recommendation

Choose one:

  • invest now
  • validate first, then invest
  • defer
  • reject

The recommendation must name what would change the call.

Output format

Return:

1. Feature summary

  • feature
  • target segment
  • decision to make

2. Value path

  • primary value mechanism
  • secondary effects

3. Cost profile

  • build cost
  • ongoing cost
  • operational implications

4. Impact scenarios

  • conservative
  • base
  • upside

5. Strategic modifiers

  • moat, compliance, platform leverage, or timing factors

6. Recommendation

  • invest now / validate first / defer / reject
  • rationale
  • biggest assumption to test next

Quick heuristics

  • If upside is modest and costs are high, default to defer unless the feature is strategically mandatory.
  • If the feature can unlock significant revenue but the adoption assumption is weak, recommend validate-first instead of immediate commitment.
  • If the feature is table stakes for a target segment, treat it as a market-access investment rather than a pure ROI play.

Quality bar

This skill is successful only if:

  • the value path is clear
  • cost includes ongoing burden, not just build effort
  • strategic arguments are separated from the financial model
  • the final recommendation is tied to specific assumptions and next evidence

Signals

GitHub stars
54
Forks
5
Last commit
May 2026
Advanced
Catalog kind
skill
Gateway key
pm-feature-investment-advisor
Source
github.com/contextgo/contextgo