{"slug":"majiayu000-architecture-research","name":"architecture-research","description":"Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed.","long_description":"---\nname: architecture-research\ndescription: \"Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed.\"\n---\n\n# Architecture Research\n\nUnderstand how real systems work before committing to a technical direction.\nProduce a decision artifact backed by inspectable evidence, not a feature table,\nvendor narrative, or speculative target architecture.\n\nRead both references before completing decision-grade work:\n\n- [Architecture lenses](references/architecture-lenses.md) explains how to\n  inspect ownership, authority, wiring, lifecycle, recovery, trade-offs, and\n  adoption risk.\n- [Evidence matrix and decision template](references/evidence-matrix.md)\n  provides the output structure.\n\n## Operating Contract\n\n- Direct actions: read-only discovery, source inspection, local experiments,\n  decision recovery, comparison, and drafting within the requested access path.\n- Escalate before: paid API use, new accounts or legal terms, publication of\n  non-public findings, remote mutations, or an unauthorized production choice.\n- Evidence-backed pushback: challenge category errors, unsupported architecture\n  claims, false equivalence, and premature hyperscale design with cited facts.\n- Feedback loop: test decisive claims, record unknowns and reversal evidence,\n  then re-open the decision when its review trigger fires.\n\n### Scope and handoff\n\nUse this skill for four related tasks:\n\n- **Landscape research**: identify and compare relevant systems or approaches.\n- **System archaeology**: reconstruct how a system actually works from source,\n  deployment material, tests, runtime evidence, and authoritative documents.\n- **Architecture decision**: choose whether to adopt, adapt, build, defer, or\n  retain the current system.\n- **Decision reassessment**: recover an earlier decision, check whether its\n  assumptions still hold, and keep or revise it using current evidence.\n\nThis skill owns external research, evidence, comparison, and the decision\nboundary. Once a direction is selected, hand detailed internal boundaries,\ncontracts, and target architecture to `architecture-foundation`. Use\n`product-discovery` for customer or market validation without a technical\ndecision question.\n\nRespect the requested access path and repository instructions. Never expose\ncredentials or reproduce private implementation details in a public artifact.\n\nDo not invoke this workflow for a small bug fix, rename, formatting change,\nroutine dependency use, or when the foundational technology is explicitly fixed\nby the user or nearest repository instructions.\n\n## Workflow\n\n### 1. State the decision question\n\nBefore searching, write a compact research brief:\n\n- User outcome and the exact capability the system must own.\n- Current boundary, missing layer, and the decision to make.\n- One or more representative quality scenarios: stimulus, operating condition,\n  expected response, and measurable success.\n- Constraints that matter now: scale horizon, freshness, latency, quality,\n  privacy, deployment, budget, licensing, data ownership, and team capacity.\n- Explicit non-goals and the cost of making no change.\n\nScale research depth to decision risk. Reversible component choices need less\nevidence than a new source of truth, data platform, hosted dependency, or\none-way migration.\n\nChallenge category errors early. A browser, API wrapper, scraper, search index,\nagent runtime, and answer engine can share a surface while owning different\ncapabilities.\n\n### 2. Recover existing context without inheriting its claims\n\nWhen prior decisions, incidents, chats, ADRs, or benchmarks exist, extract:\n\n- The decision and alternatives considered at the time.\n- Assumptions, constraints, unresolved unknowns, and promised validation.\n- What was actually implemented and what happened in operation.\n- Which facts are stale, contradicted, or were never verified.\n\nPrefer focused summaries, exact excerpts, decision records, and runtime\nartifacts over loading whole conversation archives. Treat prior conclusions as\nleads until their evidence is re-opened.\n\n### 3. Select representative alternatives\n\nSearch before proposing architecture. Include only alternatives that can change\nthe decision:\n\n- Maintained open-source systems with inspectable source and deployment paths.\n- Commercial systems with authoritative technical material.\n- Standards, public datasets, protocols, and lower-level reusable components.\n- The current system and the option to make no change.\n\nClassify each candidate as direct, adjacent, component, or non-comparable.\nDo not pad the comparison to reach an arbitrary count. Decide the possible\nreuse unit: whole system, subsystem, component, protocol, data model, or pattern.\n\n### 4. Build an evidence ledger\n\nPrefer primary evidence in this order:\n\n1. Source code, tests, manifests, schemas, releases, and reproducible runtime\n   behavior.\n2. Official technical documentation, papers, standards, patents, and\n   engineering posts.\n3. Official product, license, and pricing material for product-level claims.\n4. Independent measurements whose method, date, and environment are visible.\n\nFor current products, dependencies, pricing, licenses, or architecture, browse\nand record the date or revision. Use secondary sources only to locate primary\nevidence or to add clearly attributed independent evaluation.\n\nTag every decision-relevant claim:\n\n- **Verified**: directly supported by cited code, documentation, or measurement.\n- **Inferred**: supported by evidence but not stated directly; include the\n  reasoning and confidence.\n- **Unknown**: not revealed by available evidence; say what would resolve it.\n\nPreserve contradictions. A public SDK, plugin, or MCP server proves an interface\nexists; it does not prove that the underlying data, model, index, scheduler, or\nhosted control plane is open or independently reproducible.\n\n### 5. Trace the real system\n\nApply the relevant lenses from\n[architecture-lenses.md](references/architecture-lenses.md). At minimum answer:\n\n- What is the end-to-end path from input to user-visible result?\n- Who owns each data, control, and operational boundary?\n- What is authoritative, what is derived, and what is only ephemeral?\n- What survives restart, and how are stale or divergent states reconciled?\n- Is each claimed capability merely declared, actually implemented, wired into\n  the live path, exercised, and measured?\n- Which decisions are sensitivity or trade-off points for the named scenarios?\n\nInspect open-source implementation, tests, releases, and self-host deployment,\nnot only the README. For closed systems, draw a visible boundary around the\npublic surface and keep the hidden core unknown.\n\n### 6. Test decision-relevant claims\n\nWhen practical, run the same small representative workload against viable\noptions. Define before running:\n\n- Question, candidate versions, corpus or scenario, and expected result.\n- Scoring rule, environment, hardware, commands, and raw result location.\n- Failure behavior and recovery test when statefulness is part of the decision.\n\nMeasure the property that can change the decision: coverage, correctness,\nfreshness, extraction fidelity, latency, throughput, resource use, operability,\nor recovery. A component existing in source is not evidence that the production\npath uses it.\n\nIf a fair test cannot run, state the missing credential, dataset, environment,\nor budget and retain the uncertainty. Do not turn a vendor benchmark or demo\ninto local proof.\n\n### 7. Evaluate adoption reality\n\nFor an adoption candidate, check more than technical fit:\n\n- Maintenance and release activity, governance, contributor concentration, and\n  response to security or correctness issues.\n- License obligations, distribution model, deployment complexity, upgrade path,\n  and operational ownership.\n- Supply-chain posture, tests, release provenance, and dependency risk where\n  relevant.\n- Unit cost, switching cost, lock-in, and the exit path if the project or vendor\n  changes direction.\n\nAutomated project-health or security scores are leads, not final truth. Inspect\nthe checks, their applicability, and counterevidence.\n\n### 8. Make and bound the decision\n\nChoose one disposition for each useful idea:\n\n- **Adopt**: use the existing solution substantially as supplied.\n- **Adapt**: reuse a bounded unit while owning the differentiating layer.\n- **Build**: implement because ownership is itself required or candidates fail\n  a named constraint.\n- **Defer**: evidence is insufficient or the capability is not needed now.\n- **Retain**: keep the current system because change is not yet justified.\n\nTie the recommendation to the research brief and quality scenarios. State:\n\n- Selected direction, reuse unit, and accepted quality trade-offs.\n- Rejected alternatives and what should not be copied.\n- Risks, unknowns, and evidence that would reverse the decision.\n- Smallest validation milestone and observable success condition.\n- Exit path or review trigger for assumptions likely to change.\n- Inputs for `architecture-foundation`: selected components, constraints,\n  ownership decisions, unresolved questions, and prohibited dependencies.\n\nA long-term ambition can justify staged validation, but not speculative layers\nin the current implementation.\n\n## Common failure modes\n\n- Comparing feature names instead of system boundaries and scenarios.\n- Treating self-hostable orchestration as ownership of upstream data or models.\n- Equating a database row with a recoverable workflow or authoritative state.\n- Counting declared modules without checking wiring, execution, and measurement.\n- Assuming a public client repository contains a commercial product's core.\n- Copying hyperscale architecture before proving a bounded workload.\n- Ignoring acquisition, provenance, lifecycle, recovery, and evaluation while\n  focusing only on algorithms or storage.\n- Ranking choices with invented precision or unconfirmed weights.\n- Treating repository popularity or an automated score as adoption proof.\n- Hiding unknowns behind confident prose or silently degrading when research\n  access fails.\n\n## Done when\n\nThe decision artifact contains:\n\n- A bounded decision question, scenarios, constraints, and no-change baseline.\n- Candidate classification and a named reuse unit for viable options.\n- An evidence ledger with citations and verified/inferred/unknown labels.\n- End-to-end, ownership, authority, recovery, and capability-maturity analysis.\n- Trade-offs and decision-relevant tests, or an explicit test blocker.\n- Adoption viability when a third-party dependency is recommended.\n- An adopt/adapt/build/defer/retain decision, rejected alternatives, accepted\n  risks, reversal evidence, exit or review trigger, and smallest milestone.\n\nBefore claiming completion, re-open decisive sources, check dates and revisions,\nand run repository-required validation for any changed files.\n","tagline":"Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an","category":"research","tags":["agent-skill"],"author":"majiayu000","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"github fast track","sourceDetail":"majiayu000/spellbook","creatorName":"majiayu000","creatorUrl":"https://github.com/majiayu000","sourceUrl":"https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/majiayu000-architecture-research#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals."},"stats":{"stars":265,"forks":26,"verified_installs":0,"successful_runs":0,"total_outcomes":0,"rating":0,"review_count":0,"quality_score":40.07},"quality":{"score":71,"tier":"strong","label":"Strong","summary":"Solid option that is likely worth shortlisting for production workflows.","signals":[{"label":"GitHub stars","value":"265","tone":"neutral"},{"label":"Freshness","value":"6d ago","tone":"positive"},{"label":"Install ready","value":"Yes","tone":"positive"},{"label":"License","value":"MIT","tone":"neutral"}],"warnings":[]},"trust":{"version":"trust-score-v5","score":67,"base_score":75,"outcome_confidence":0,"tier":"review","label":"Sandbox only","summary":"Useful candidate with missing or mixed trust signals. 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Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed.","category":"research","url":"https://www.openagentskill.com/skills/majiayu000-architecture-research","repository":"https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research","github_repo":"majiayu000/spellbook"},"suited_tasks":["Research agents workflows","Claude Code teams","builders willing to evaluate younger projects","Search sources","Extract claims","Synthesize findings","Inspect repository metadata","Compare code changes"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","Browser agents","CLI"],"install":{"command":"npx skills add majiayu000/spellbook --skill architecture-research","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add majiayu000-architecture-research"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"architecture-research\" agent skill from https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"majiayu000-architecture-research\",\"task\":\"Install architecture-research\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"architecture-research\" as a Claude Code skill from https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"majiayu000-architecture-research\",\"task\":\"Install architecture-research\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"architecture-research\" from https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"majiayu000-architecture-research\",\"task\":\"Install architecture-research\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/majiayu000-architecture-research/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/majiayu000-architecture-research"},"trust":{"score":75,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"265 GitHub stars","repoActivity":"265 stars, 26 forks","lastPushed":"6d since push","license":"MIT","repository":"https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research","install":"npx skills add majiayu000/spellbook --skill architecture-research","installSafety":"standard package or runtime install path","permissionSurface":"secrets or environment access, filesystem or document access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["research","agent-skill"],"known_risks":["Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: secrets or environment access, filesystem or document access","Stars/forks activity: 265 stars, 26 forks; issue activity unavailable in current metadata","Dependency/runtime risk: credential or environment access, network or browser surface","Permission surface: secrets or environment access, filesystem or document access"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":80,"risk_level":"needs_review","risk_label":"Needs review","warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: secrets or environment access, filesystem or document access","Stars/forks activity: 265 stars, 26 forks; issue activity unavailable in current metadata","Dependency/runtime risk: credential or environment access, network or browser surface"]},"safety_gate":{"tier":"experimental","label":"Experimental","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Test manually in an isolated workspace and compare against safer alternatives."},"quality":{"score":71,"label":"Strong"},"supply":{"track":"Research and knowledge work","scenario":"Research agents","maintenance":"6d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No OpenAgentSkill engagement data yet","High-risk permission hints: Secrets or environment access","Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision."],"agent_contract":{"task_input":"Use architecture-research in an agent workflow","recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","install_policy":"review","minimum_review_before_use":["Trust: 75/100 Strong shortlist","Audit: 80/100 Needs review","Safety: 44/100 Avoid automatic install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"majiayu000-architecture-research (architecture-research)","install_command":"npx skills add majiayu000/spellbook --skill architecture-research","risk_summary":"Needs review; Experimental; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"majiayu000-architecture-research","task":"Use architecture-research in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/majiayu000-architecture-research","api":"https://www.openagentskill.com/api/agent/skills/majiayu000-architecture-research","audit":"https://www.openagentskill.com/skills/majiayu000-architecture-research/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=majiayu000-architecture-research&task=Use%20architecture-research%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20architecture-research%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20architecture-research%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/majiayu000-architecture-research/install","manifest":"https://www.openagentskill.com/api/registry/manifest/majiayu000-architecture-research"}},"supply_profile":{"track":{"slug":"research","label":"Research and knowledge work","shortLabel":"Research","description":"Deep research, source comparison, literature review, RAG, knowledge search, and reports."},"scenario":{"label":"Research agents","description":"I need my agent to research a topic, compare sources, and produce a concise report.","useCases":[{"slug":"research-agents","title":"Research agents"},{"slug":"github-automation","title":"GitHub automation"},{"slug":"legal-compliance","title":"Legal and compliance"}]},"applicableAgents":["Claude Code","Browser agents","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add majiayu000/spellbook --skill architecture-research","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":265,"starsLabel":"265","forks":26,"license":"MIT","qualityScore":71,"trustScore":75,"auditScore":80},"maintenance":{"status":"fresh","label":"6d since push","daysSincePush":6,"lastPushedAt":"2026-08-31T15:38:47+00:00"},"risk":{"level":"needs_review","label":"Needs review","requiresReview":true,"notes":["Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review"]},"coverageTags":["Research","Research agents","agent-skill"]},"audit":{"audit_score":80,"risk_level":"needs_review","risk_label":"Needs review","quality_score":71,"trust_score":75,"maintenance_score":100,"security_score":78,"install_score":92,"warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: secrets or environment access, filesystem or document access","Stars/forks activity: 265 stars, 26 forks; issue activity unavailable in current metadata","Dependency/runtime risk: credential or environment access, network or browser surface","Permission surface: secrets or environment access, filesystem or document access"]},"quality_signals":{"model":"v2","star_score":16.97,"usage_score":0,"review_score":5.1,"metadata_score":3,"freshness_score":15},"platforms":["Claude Code","Browser agents"],"use_cases":[{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"},{"slug":"github-automation","title":"GitHub automation","url":"https://www.openagentskill.com/use-cases/github-automation"},{"slug":"legal-compliance","title":"Legal and compliance","url":"https://www.openagentskill.com/use-cases/legal-compliance"},{"slug":"web-scraping","title":"Web scraping","url":"https://www.openagentskill.com/use-cases/web-scraping"}],"stacks":[{"slug":"research-report-agent","title":"Research report agent","url":"https://www.openagentskill.com/collections/research-report-agent"},{"slug":"web-data-pipeline","title":"Web data pipeline","url":"https://www.openagentskill.com/collections/web-data-pipeline"},{"slug":"browser-qa-agent","title":"Browser QA agent","url":"https://www.openagentskill.com/collections/browser-qa-agent"}],"install":"npx skills add majiayu000/spellbook --skill architecture-research","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add majiayu000-architecture-research","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"architecture-research\" agent skill from https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"majiayu000-architecture-research\",\"task\":\"Install architecture-research\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"architecture-research\" as a Claude Code skill from https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"majiayu000-architecture-research\",\"task\":\"Install architecture-research\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"architecture-research\" from https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"majiayu000-architecture-research\",\"task\":\"Install architecture-research\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research","github_repo":"majiayu000/spellbook","version":"1.0.0","license":"MIT","urls":{"web":"https://www.openagentskill.com/skills/majiayu000-architecture-research","repository":"https://github.com/majiayu000/spellbook/tree/main/skills/architecture-research","api":"/api/agent/skills/majiayu000-architecture-research","install_api":"/api/skills/majiayu000-architecture-research/install"},"meta":{"created_at":"2026-09-03T16:35:01.125575+00:00","updated_at":"2026-09-03T16:35:01.203618+00:00","agent_friendly":true}}