How do I install the Fpf Strategize skill?

Run npx skillmds@latest add m0n0x41d/fpf-strategize 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 Fpf Strategize safe to use?

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Which AI agents work with Fpf Strategize?

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 Fpf Strategize free to use?

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

Who published Fpf Strategize?

m0n0x41d (@m0n0x41d) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Fpf Strategize by m0n0x41d — Agent Skill

Name: Fpf Strategize
Author: m0n0x41d

File contents

What this skill IS

This is strategic betting, not variant selection. You are choosing which class of approach to bet on — scoping the search space for variant generation. "We'll explore variants within [family X] because [reason]."

Strategizing ≠ SoTA survey. SoTA maps the landscape; strategizing bets on a region. Strategizing ≠ variant selection. Strategy scopes the family; selection picks from generated variants.

Prerequisites

PROB-* or ANOM-* exists with acceptance spec
SOTA-* exists (if missing: invoke /fpf-sota first)

Output

.fpf/decisions/STRAT-${CLAUDE_SESSION_ID}--<slug>.md

Constraints (quality bar)

C1: ≥2 candidate method families evaluated
C2: Each family assessed for admissibility against PROB-* constraints
C3: Primary bet stated with rationale (why this family over others)
C4: Variant generation axes defined (what will differ between variants within this family)
C5: Invalidation conditions stated (what would cause a pivot to different family)
C6: Links to PROB-* and SOTA-*
C7: Scaling-Law Lens (SLL): for each family, state how it scales with more resources (compute/data/time). Minimum two measurement points (Scale-Probe) to claim a slope. Elasticity class: growing | plateau | declining. At comparable budgets, prefer the family with better scaling slopes (BLP — Bitter Lesson Preference).

Format

# Strategy Card
- **ID:** STRAT-...  **Problem:** PROB-...  **SoTA:** SOTA-...
- **valid_until:** YYYY-MM-DD

## Candidate families
| # | Family | Admissible? | Scaling (SLL) | Key risks |
| F1 | ... | Y/N | growing/plateau/declining | ... |
| F2 | ... | Y/N | growing/plateau/declining | ... |

## Bet
Primary: [family]. Rationale: ...

## Variant generation axes
(diversity dimensions within chosen family)

## Invalidation conditions
(what would cause a pivot)

## valid_until
(when does this strategy bet go stale? Tech landscape changes, new SoTA emerges)

---name: fpf-strategizedescription: Bet on a method family — choose WHICH CLASS of approach to explore, not which specific solution. First-class creative act. MUST invoke for T4 architectural work before variant generation.---## What this skill ISThis is **strategic betting**, not variant selection. You are choosing which class of approach to bet on — scoping the search space for variant generation. "We'll explore variants within [family X] because [reason]."**Strategizing ≠ SoTA survey.** SoTA maps the landscape; strategizing bets on a region.**Strategizing ≠ variant selection.** Strategy scopes the family; selection picks from generated variants.## Prerequisites- PROB-* or ANOM-* exists with acceptance spec- SOTA-* exists (if missing: invoke `/fpf-sota` first)## Output`.fpf/decisions/STRAT-${CLAUDE_SESSION_ID}--<slug>.md`## Constraints (quality bar)- **C1:** ≥2 candidate method families evaluated- **C2:** Each family assessed for admissibility against PROB-* constraints- **C3:** Primary bet stated with rationale (why this family over others)- **C4:** Variant generation axes defined (what will differ between variants within this family)- **C5:** Invalidation conditions stated (what would cause a pivot to different family)- **C6:** Links to PROB-* and SOTA-*- **C7:** Scaling-Law Lens (SLL): for each family, state how it scales with more resources (compute/data/time). Minimum two measurement points (Scale-Probe) to claim a slope. Elasticity class: growing | plateau | declining. At comparable budgets, prefer the family with better scaling slopes (BLP — Bitter Lesson Preference).## Format```markdown# Strategy Card- **ID:** STRAT-... **Problem:** PROB-... **SoTA:** SOTA-...- **valid_until:** YYYY-MM-DD## Candidate families| # | Family | Admissible? | Scaling (SLL) | Key risks || F1 | ... | Y/N | growing/plateau/declining | ... || F2 | ... | Y/N | growing/plateau/declining | ... |## BetPrimary: [family]. Rationale: ...## Variant generation axes(diversity dimensions within chosen family)## Invalidation conditions(what would cause a pivot)## valid_until(when does this strategy bet go stale? Tech landscape changes, new SoTA emerges)```

Frequently asked questions

Fpf Strategize