OST Target Selection

SkillDev tools

Select one target opportunity from an OST using evidence-based weighted scoring and tie-breakers.

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 OST Target Selection skill

What this skill tells your AI

The instructions your AI receives, as published by itseffi/agentic-os in .agents/skills/ost-target-selection/SKILL.md and read by ahel’s review.

Choose exactly one opportunity to pursue next.

Instructions

Step 1: Harvest candidates from OST

  • Include leaves and relevant parents with strong evidence.
  • Merge duplicates and reframe solution language into need language.

Step 2: Score candidates

  • Score 1-5 for OS, MF, CF, CuF.
  • Use default weights unless custom weights are provided.
  • Compute weighted priority score (WPS).

Step 3: Build shortlist

  • Select top 3-5 by WPS.
  • Apply tie-breakers: distinctness, evidence quality, time-to-learning, risk diversification.

Step 4: Recommend one target

  • Pick one small, distinct, moment-scoped opportunity.
  • Exclude engineering effort prioritization.

Step 5: Audit alignment

  • Confirm no-effort-policy and moment distinctness.
  • List evidence gaps and follow-up needs.

Output

  • Candidate inventory
  • Scoring matrix with WPS
  • Top 3-5 shortlist
  • Single recommendation with rationale
  • Audit notes

When to Use

Use this skill when the task directly matches the workflow described above.

When Not to Use

Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.

Signals

GitHub stars
112
Forks
21
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
ost-target-selection
Source
github.com/itseffi/agentic-os