Tier 4

p10useful - Pick 10 Useful

Pick 10 Useful

Input: $ARGUMENTS

Core Principles

  1. Usefulness is breadth times depth. A skill is useful if it applies to many situations (breadth) AND produces substantial output when it does (depth). High breadth + low depth = superficial. Low breadth + high depth = niche. High both = useful.

  2. Connectivity is a signal. Skills that invoke many other skills or are invoked by many other skills sit at network hubs. Hub skills are useful because they are entry points to larger capability chains.

  3. Tier reflects community validation. Higher-tier skills have survived more usage and refinement. Tier is not a perfect proxy for usefulness, but it is a strong prior.

  4. Category diversity prevents echo chambers. The 10 most useful skills should not all be analysis skills. Cap any single category at 3 to ensure the user gets a well-rounded toolkit.

  5. The list should be defensible. For each pick, you should be able to answer: “If a new user could only learn 10 skills, why THIS one?” If you can’t answer that, the pick is not in the top 10.

Phase 1: Universal Scoring

Score every skill in the library on four dimensions.

[A] SCORING_DIMENSIONS:

For each skill:

1. TIER_SCORE:
    tier1 = 10
    tier2 = 8
    category = 7
    experimental = 6
    tier3 = 4
    tier4 = 2

2. CONNECTIVITY:
    Count of (invokes + invoked_by)
    Skills with 0 connections = 0
    Skills with 1-3 connections = 2
    Skills with 4-7 connections = 4
    Skills with 8+ connections = 6

3. BREADTH:
    Count of non-empty categories + count of tags
    0-2 = 1
    3-5 = 2
    6-8 = 3
    9+ = 4

4. DEPTH_PROXY:
    line_count > 200 = 4
    line_count 100-200 = 3
    line_count 50-100 = 2
    line_count < 50 = 1

TOTAL = TIER_SCORE + CONNECTIVITY + BREADTH + DEPTH_PROXY

Phase 2: Ranking and Diversity Enforcement

[B] RANKING:

Step 1: Sort all skills by TOTAL score (descending)
Step 2: Take top 10

Step 3: DIVERSITY CHECK:
    Count skills per category in the top 10
    IF any category has > 3 skills:
        → Remove the lowest-scoring excess skills from that category
        → Replace with the highest-scoring skills from underrepresented categories
    Repeat until no category has > 3 skills

Step 4: FUNCTION CHECK:
    Verify at least 4 of these functions are represented:
    [analysis / decision / planning / creation / validation / exploration / diagnosis]
    IF < 4:
        → Swap lowest-scoring pick for highest-scoring from missing function

Phase 3: Justification

For each of the 10 picks, generate a defensible justification.

[C] JUSTIFICATIONS:

For each pick:
    QUESTION: "If a new user could only learn 10 skills, why this one?"
    ANSWER: [1-2 sentence justification]
    SCORE_BREAKDOWN: tier=[X] + connectivity=[Y] + breadth=[Z] + depth=[W] = [total]
    UNIQUE_VALUE: [what does this skill do that no other top-10 skill does?]

Phase 4: Output

ALGORITHM: USEFUL
POOL: [total skills scored]
PICKED: 10

TOP 10 MOST USEFUL SKILLS:
  1. /[id] — [title] — Score: [X] (tier=[T], connections=[C], breadth=[B], depth=[D])
     [1-line description]
     Why top 10: [justification]

  2. /[id] — [title] — Score: [X] (tier=[T], connections=[C], breadth=[B], depth=[D])
     [1-line description]
     Why top 10: [justification]

  [continue to 10...]

CATEGORY DISTRIBUTION:
  [category]: [N picks]
  [category]: [N picks]
  ...

FUNCTION COVERAGE:
  [analysis/decision/planning/creation/validation/exploration/diagnosis]: [which are covered]

HONORABLE MENTIONS (skills 11-15):
  11. /[id] — [title] — Score: [X]
  12. ...

NOTABLE ABSENCES:
  [any skill type or category conspicuously missing from the top 10]
  To fill: /[suggested skill]

Failure Modes

FailureSignalFix
Category clustering5+ picks from analysis or decision skillsEnforce 3-per-category cap
Tier-only rankingTop 10 are just the 10 highest-tier skills regardless of connectivity/breadthAll 4 scoring dimensions must contribute
No justificationPicks listed without explaining why they’re useful”Why top 10?” answer is mandatory for each
Stale resultsSame 10 every time regardless of library changesScore should reflect current skills.json state
Missing functionsAll picks are analytical — no decision, planning, or creation skillsFunction check is mandatory
Line count gamingLong but shallow skill scores high on depth proxyDepth proxy is line_count, but justification checks actual quality

Depth Scaling

DepthScoringRankingJustification
1xTier + connectivity onlyTop 10 with category cap1-line descriptions
2xAll 4 dimensionsTop 10 + diversity + function checkFull justifications + honorable mentions
4x4 dimensions + quality audit of candidatesOptimized ranking with diversity/function iterationJustifications + notable absences + comparison
8xFull library audit with quality-adjusted scoresMulti-pass ranking with cross-validationDefensible essay per pick + alternative top-10 sets

Default: 2x. These are floors.

Pre-Completion Checklist

  • All skills scored on 4 dimensions (tier, connectivity, breadth, depth)
  • Top 10 selected with diversity enforcement (no category > 3)
  • At least 4 functions represented in the top 10
  • Each pick has a defensible “why top 10” justification
  • Exactly 10 skills returned
  • Score breakdown shown for each pick
  • Honorable mentions (11-15) included
  • Notable absences identified

Integration

  • Shortcut for: /pick 10 useful
  • Use when: You want the objectively best general-purpose skills
  • Routes to: The 10 picked skills; /p10diverse for coverage-maximizing alternative
  • Related: /p10diverse (coverage over quality), /p10random (serendipity over quality)
  • Differs from /p10diverse: diverse maximizes coverage; useful maximizes quality
  • Differs from /p10random: random has no quality bias; useful is entirely quality-driven
  • Differs from /p10goal: goal matches to a specific purpose; useful is purpose-agnostic