quantipixels/skills

arojinle

Resolve consequential choices through a relentless, complete decision-tree interview and final user confirmation.

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Àròjinlẹ̀

Use amose when unresolved project-specific meaning—terms, identities, boundaries, relationships, ownership, or invariants—can materially change the decision tree.

Interview the user relentlessly until shared understanding is reached and no consequential branch remains silently assumed. Map it as a decision tree: every decision branches into the decisions that depend on it.

Work the tree in rounds. The frontier is every decision whose prerequisites are already settled. Ask the whole answerable frontier in one round, then wait for the user's answers before starting the next.

Present each round in the conversation using numbered question blocks, separated by horizontal rules:

markdown
❓ **Q<n> - <topic>**
<question, enough context to answer, and choices where useful>

➡️ **Recommendation:** <answer and reason>

Each round reshapes the tree. Recompute the material frontier from confirmed answers before asking the next round; answers may create, remove, merge, split, or reframe dependent branches. Do not merely continue the previously imagined tree.

Do not ask a question whose answer depends on another still-open question in the same round.

Finding facts is your job, never the user's. Resolve bounded facts directly. While subagents investigate a prerequisite, ask independent frontier questions now; only questions depending on that evidence wait.

Delegate substantial analysis, research, and expert work to subagents, returning concise findings and evidence links to keep the main context lean.

Use other skills as needed to form or resolve frontier decisions; continue the same interview.

When a frontier choice has several credible alternatives and at least two independent criteria can materially change the recommendation, use a compact decision-specific rubric. Apply hard gates first; derive only the criteria that matter to this decision; show the decisive factor, strongest credible alternative, and material counterevidence. Do not manufacture scores for a trivial/already-determined choice or let an average hide a gate. The rubric supports the recommendation; the decision remains the user's.

Use atona in exploration mode and prototype as needed.

The decisions remain the user's. Do not silently convert a recommendation, generated option, comparative grade, or prototype observation into confirmation.

Visual support proportionality

Use html-artifact as needed. Preserve hard gates, uncertainty, and counterevidence in visual comparisons.

Before declaring the material frontier empty, challenge the current tree for consequential assumptions, missing branches, contradictory decisions, and dependencies that were never made explicit.

Finish only when that challenge leaves no unresolved material branch and the user confirms shared understanding. Return confirmed decisions, material assumptions/evidence, decision-changing alternatives/criteria when they constrained the choice, explicit deferrals/re-entry conditions, and the next outcome boundary. Do not execute resulting delivery inside arojinle.

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alaga

Build and verify an accepted coding change or fix. Use directly when the outcome is sufficiently clear, or within an atona initiative; exclude initiative coordination, standalone planning, review, and publication.

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1
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0
最近更新
9月13日
quantipixels
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alarina

Guide requested work through completion using relevant installed skills and conditional routes. Use as the operating entrypoint for skill-driven work, to choose the next owner, resume work, resolve adjacent ownership, or request the installed skill inventory.

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1
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0
最近更新
9月13日
quantipixels
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amose

Establish, sharpen, or reconcile one project's canonical domain model and its durable records. Use when project-specific terms, conceptual identities, domain/context boundaries, relationships, ownership, invariants, .learnings, .nongoals, or ADRs need to be defined, changed, or maintained.

安装量
1
GitHub Stars
0
最近更新
9月13日
quantipixels
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architect

Design, survey, or review the technical structure of a software system or consequential module at the smallest scale needed to resolve the architecture question. Use for architectural friction, system boundaries, module/interface/seam shape, data/state ownership, integrations, deployment, quality scenarios, trade-offs, migration/recovery, or architecture sufficiency; exclude initiative lifecycle planning, user-decision closure, implementation, workspace infrastructure, and code-review verdicts.

安装量
1
GitHub Stars
0
最近更新
9月13日