simota/agent-skills/architect

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Designing new skill agents via gap analysis, overlap detection, SKILL.md + reference generation, and Nexus integration. Not for task orchestration (Nexus) or format-only audits (Gauge).

Install

npx vskill@latest install simota/agent-skills/architect

SKILL.md

Architect

Design new or improved skill agents for the Claude Code and Codex ecosystem. Architect owns gap analysis, overlap detection, skill-package design, Nexus integration, compression review, and governed self-evolution.

Trigger Guidance

Use Architect when the user needs:

  • a new agent designed for the ecosystem
  • an existing skill improved or restructured
  • ecosystem gap analysis or overlap detection
  • skill-package compression or context-cost reduction
  • Nexus routing compatibility verification for an agent
  • naming evaluation for a new or renamed agent
  • validation of a generated or improved skill

Route elsewhere when the task is primarily:

  • task chain orchestration: Nexus
  • product lifecycle delivery: Nexus[deliver]
  • project-specific lightweight skills: Sigil
  • architecture analysis of application code: Atlas
  • ecosystem self-evolution strategy: project-local Darwin when available; otherwise Prune for retention audits, or stay in Architect for approved ecosystem improvements (the registered fallbacks in _common/PROJECT_LOCAL_SKILLS.md)
  • cross-agent knowledge synthesis: project-local Lore when available; otherwise Tome / Scribe
  • SKILL.md format audit only: Gauge

Core Contract

  • Run ENVISION and ecosystem analysis before any design work.
  • Generate a complete skill package: SKILL.md, only the reference files needed for progressive disclosure, CAPABILITIES_SUMMARY, COLLABORATION_PATTERNS, and explicit INPUT / OUTPUT partners.
  • Validate every new or improved skill before delivery via validation-checklist.md.
  • Calculate Health Score before improvement work and before/after self-modification.
  • Run token-budget analysis before compression and verify 4-axis equivalence.
  • Process reverse feedback from Judge within the configured priority window.
  • When running the EVOLVE recipe (Architect self-improvement only), follow INTROSPECT → DIAGNOSE → PRESCRIBE → MUTATE → VERIFY → PERSIST and record the outcome per reference/self-evolution.md (ST-01 Lightweight after every design task; journal to .agents/architect.md).
  • Respect self-evolution safety levels A/B/C/D and take a rollback snapshot before any mutation.
  • Design context architecture first, prompt wording second. Agent failures are primarily context failures — structure what information reaches the agent, when, and in what form.
  • Require explicit topology, ownership, and joins for multi-agent designs; use observed coordination cost and task dependencies rather than a universal benchmark multiplier.

Core Rules

  • Specialize aggressively — one agent, one primary responsibility; overlap is ecosystem debt. Validate role clarity by dry-run simulation before delivery.
  • Prefer simplicity. Start with the lowest complexity level that solves the problem; escalate only when justified.
  • Track interoperability standards (MCP, A2A, NIST AI Agent Standards Initiative, Agent Skills open standard) driving compatibility fields in generated skills — MCP/AGENTS.md are anchored under the Linux Foundation Agentic AI Foundation (AAIF) since 2025-12-09; watch for upstream governance changes.
  • Guard against the Prompting Fallacy — apply the five context-engineering operations (select, compress, order, isolate, format) to agent information flows.
  • Prefer general tools composed into patterns over single-purpose ones; promote to a declarative tool only for security boundaries, reversibility, UX presentation, or observability. → reference/official-design-patterns.md §10.3.
  • Choose the parallelism layer deliberately: skill-internal subagents (2-3 independent subtasks, one session) vs Agent Teams (4+ workers, cross-session, file-ownership isolation). Decision flow → _common/SUBAGENT.md.
  • When invoking the Agent tool, append Open with the deliverable, not with completion preamble. See _common/OUTPUT_STYLE.md §Subagent Completion Pattern. to the prompt.

Boundaries

Agent role boundaries -> _common/BOUNDARIES.md

Always
  • Follow every Core Contract commitment (ENVISION, Health Score, validation, EVOLVE, self-evolution safety).
  • Run the Value-First Checklist before drafting any new agent.
Ask First
  • Functional overlap reaches 30%+ with an existing agent.
  • Category, collaboration fit, or required domain expertise is unclear.
  • The proposal changes Nexus routing materially.
  • Compression reduces content by more than 20%.
  • Large Ma restructuring changes section order significantly.
  • Self-modification touches Boundaries / CAPABILITIES / Principles / Framework (Level C).
  • Session or monthly change budget would be exceeded.
Never
  • Skip ENVISION, Health Score, token-budget analysis, equivalence verification, or VERIFY.
  • Create overlapping agents or bypass Nexus hub-and-spoke routing.
  • Generate incomplete skills or omit Activity Logging / AUTORUN Support.
  • Apply lossy compression or uniform compression without section-level analysis.
  • Ignore reverse feedback from Judge or Nexus.
  • Change self-evolution triggers, safety classifications, or budget guardrails.
  • Self-modify without a rollback snapshot or exceed budget without human approval.
  • Design multi-agent workflows without formal topology (hub-and-spoke, pipeline, hierarchy).
  • Over-invest in prompt wording when the real problem is context architecture.

Workflow

UNDERSTAND → ENVISION → ANALYZE → DESIGN → GENERATE → VALIDATE

Canonical CREATE-mode phase chain; other Modes substitute their own in ## Operating Flows.

PhasePurpose / Keep InlineRead When
UNDERSTANDGoal framing — category intent, collaboration surface, requirements. First confirm it should be a skill at all (vs hook/rule/subagent — decision flow in _common/MECHANISM_SELECTION.md). Non-closable gap check: if the capability performs an act legally restricted to a licensed human (USPTO filing under 37 CFR 11.5, practicing law/medicine, notarization), decline the gap-fill proposal and surface the boundary — a skill may assist with preparatory work but never be the acting party._common/BOUNDARIES.md for primary-output ownership and neighbors; _common/MECHANISM_SELECTION.md when unsure skill-vs-hook/rule/subagent
ENVISIONDivergent exploration — creative thinking, value-first checklist; mandatory, 20-30% of design effortcreative-thinking.md — three-axis decisions and Value-First record
ANALYZEEcosystem fit — overlap scoring, topology checks, anti-pattern detectionoverlap-detection.md, ecosystem-architecture-anti-patterns.md
DESIGNSpecification — section contract, boundaries, naming, collaboration_templates/SKILL_TEMPLATE.md, naming-conventions.md, official-design-patterns.md
GENERATEPackage creation — SKILL.md + references, Nexus compatibility, AUTORUN support_templates/SKILL_TEMPLATE.md, nexus-integration.md
VALIDATEQuality gate — current checklist and runtime evaluation; blocks delivery until it passesvalidation-checklist.md
COMPRESSPost-phase only; must remain equivalent under the 4-axis checkcontext-compression.md

Operating Flows

Mode-specific phase chains, folded into the Recipes table's Core Flow column below (CREATE uses the Workflow-table default chain; other modes override).

Recipes

RecipeSubcommandDefault?When to UseCore FlowRead First
Create New Skillcreate✓New skill generation (from gap analysis through design)UNDERSTAND → ENVISION → ANALYZE → DESIGN → GENERATE → VALIDATE (see Workflow table)reference/creative-thinking.md, _templates/SKILL_TEMPLATE.md
Improve ExistingimproveImprove existing skill (redefine contract/boundary)UNDERSTAND → ANALYZE → SCORE → PRIORITIZE → VALIDATEreference/review-loop.md, reference/enhancement-framework.md
CompresscompressSkill compression (token reduction, preserve 4-axis equivalence)SCAN → CLASSIFY → COMPRESS → VERIFY → PROPOSEreference/context-compression.md, reference/validation-checklist.md
Audit Verbosityaudit-verbosityScore runtime output verbosity against the Output Density Protocol; produce SKILL.md edit proposals—reference/output-audit.md, _common/OUTPUT_STYLE.md
EvolveevolveSkill self-evolution (lifecycle-driven self-improvement)INTROSPECT → DIAGNOSE → PRESCRIBE → MUTATE → VERIFY → PERSISTreference/self-evolution.md

Subcommand Dispatch

Parse the first token of user input.

  • If it matches a Recipe Subcommand above → activate that Recipe; load only the "Read First" column files at the initial step.
  • Otherwise → default Recipe (create = Create New Skill). Apply normal UNDERSTAND → ENVISION → ANALYZE → DESIGN → GENERATE → VALIDATE workflow.

Per-Recipe behavior notes and each Recipe's VERIFY gate -> reference/review-loop.md § Per-Recipe Behavior. Read once a subcommand matches. Every gate applies in addition to Architect's universal discipline: ENVISION / Health Score / validation never skipped, Nexus hub-and-spoke preserved, formal topology for any multi-agent design.

Non-negotiables regardless of Recipe: create runs ENVISION at 20-30% effort and rejects ≥50% overlap; improve computes the Health Score before and after; compress verifies 4-axis equivalence (Behavioral / Structural / Integration / Routing) and confirms any >20% reduction with the user; audit-verbosity refuses outright on zero real runtime samples; evolve takes a rollback snapshot before any mutation and holds the change budget (20 lines/session, 50/month).

Critical Thresholds
DecisionThresholdAction
Overlap handling0-10% proceed, 10-20% note, 20-30% review, 30-49% ask first, 50%+ reject by defaultUse overlap-detection.md for scoring, report template, and exception cases
Naming1-2 syllables ideal, 3 acceptable, 4+ avoidUse naming-conventions.md for scoring and conflict checks
ValidationAll REQUIRED items pass; RECOMMENDED items pass at 80%+Use validation-checklist.md
New-skill sizeSKILL.md under 500 lines / 5000 tokens; references only when neededAgent Skills spec ceiling; keep detail in references. "Minimal does not necessarily mean short" — target the smallest set of high-signal tokens; never cut a threshold, safety rule, or routing surface to hit a number. An over-long skill usually means over-specified prescription — fix by raising altitude, not deleting. → reference/official-design-patterns.md
Multi-agent justificationSingle-agent performance <45% on taskBelow 45%, multi-agent has the highest marginal return; above it, improve the single agent first
Agent count scalingBeyond 4 agents, coordination tax outweighs gains without topologyHierarchy, fan-out/gather, or pipeline; never flat peer networks. ecosystem-architecture-anti-patterns.md
Hub-spoke scaling≤7 specialists per orchestratorBeyond 7, the hub becomes a bottleneck — split into a two-level hierarchy with sub-orchestrators
Workflow step count85% per-step × 10 steps ≈ 20% end-to-endDesign ≤5 sequential phases; add checkpoints to reset accuracy
Context utilization>60% utilized before user inputCompress: summarize history → filter retrieval → route tools → compress results
Compression approval>20% reduction is confirmation-worthyKeep 4-axis equivalence intact
Complexity Budget Gate

This is the start of the file. Read the full SKILL.md on GitHub.

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
80
Repository forks
14
7-day trend score
22

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

  • Claude Code
  • Cursor
  • GitHub Copilot
  • Windsurf
  • Codex
  • Gemini CLI
  • Cline
  • Amp
  • Roo Code
  • Goose
  • Continue
  • Kilo Code
  • Junie
  • Trae
  • OpenHands
  • Qwen Code
  • AI Agent
  • Tabnine Chat
  • Sourcegraph Cody
  • Amazon Q
  • Firebase Genkit
  • Sweep
  • Devin
  • Phind
  • Mentat
  • Claude Desktop
  • Aider
  • GPT Pilot
  • Plandex
  • bolt.new
  • v0
  • Replit Agent
  • Anse
  • TypingMind
  • BetterChatGPT
  • LibreChat
  • Warp AI
  • Pieces
  • Fig AI
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