using-overpowered

Part of the Overpowered skill suite. Route knowledge-work and enterprise-automation tasks through the smallest relevant combination of Overpowered skills, and invoke gear-up only when a material execution capability is genuinely missing. Use when multiple suite skills may apply or when starting a non-trivial task involving organizational knowledge, conflicting evidence, evolving artifacts, business rules, process automation, risky side effects, verifiable completion, or an uncovered capability gap.

Overpowered / Using Overpowered

Purpose

Apply the smallest set of Overpowered working methods that materially improves the task. Select process/knowledge skills before implementation mechanics; never load the suite by default and never create a new capability merely because creation is possible.

Routing protocol

Before substantial action, scan these conditions:

Condition	Use
Material organization-specific/current/historical knowledge is missing	know-enough
Prior cases may help	find-precedent
Answer lives in structured files	ask-the-data
Sources materially disagree	reconcile
Versions/snapshots must be compared	what-changed
Plan depends on hidden premises	assumption-audit
Rules/process have likely non-happy paths	find-the-exceptions
Human process should become executable automation	automate-this
Human authority/risk boundary must be designed	human-gates
Side effects are broad/irreversible/costly	dry-run
Material claims need traceability	evidence-first
Work is about to be declared complete	completion-audit
Work must survive a context/harness boundary	checkpoint
A material execution gap remains after reuse/knowledge/Academy checks	gear-up
A qualified/proven workflow should become a durable portable skill	skillify

Priority rules

1. Understand before automating. If a process is underspecified, use find-the-exceptions before automate-this finalizes the design.
2. Know before guessing. Use know-enough when retrieval can resolve a material uncertainty.
3. Authority before analogy. Current authoritative knowledge outranks precedent for normative questions.
4. Conflict before synthesis. Reconcile material disagreement before producing a single “truth.”
5. Reuse before creation. Installed skills/tools, generic runtime capabilities, and relevant Academy candidates outrank gear-up generation.
6. Create only for a proven capability gap. Missing knowledge, convenience, token pressure, or a long prompt are not capability gaps.
7. Simulation before risky side effects. Use dry-run when a preview meaningfully reduces risk.
8. Evidence before completion. Use completion-audit before strong done/fixed/migrated/reconciled claims.

Do not over-compose

Do not invoke the whole suite. Typical chains are 1–4 skills. gear-up is a last-mile fallback, not a default member of a chain.

Examples:

text

contract clause
→ know-enough → find-precedent → human-gates

policy revision
→ what-changed → know-enough

business process automation
→ find-the-exceptions → automate-this → dry-run

data question
→ ask-the-data → completion-audit only if a strong completion claim matters

missing deterministic operation during a real task
→ reuse/search → gear-up → validate/use → Academy candidate only if valuable

Interaction rule

If a skill can discover a fact from tools or artifacts, do not ask the user for that fact. Ask humans for intent, decisions, unavailable tacit knowledge, authority, or approval required by risk policy.

Adaptive capability rule

Before gear-up, be able to state all of the following in one short block:

text

Material objective at risk: ...
Why existing capabilities are insufficient: ...
Why this is not a knowledge gap: ...
Academy reuse result: ...
Smallest missing capability: ...
Observable value test: ...

If that block cannot be completed credibly, do not generate a new capability.

Stop condition

Stop routing once the active skill set and existing runtime capabilities cover the material failure modes of the current task. Then execute. If a proven execution gap remains, route once through gear-up; do not continue meta-analysis or capability generation after the task can proceed reliably.