System Design Baseline Builder

SkillMedia

Creates a project baseline of architecture drivers and constraints. Use before design or planning; not for target design, plan review, implementation, or architecture audit.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the System Design Baseline Builder skill

What this skill tells your AI

The instructions your AI receives, as published by levnikolaevich/claude-code-skills in plugins/architecture-suite/skills/ln-71-system-design-baseline-builder/SKILL.md and read by ahel’s review.

Goal: Create or update one durable source of truth for the project's architecture-driving requirements and constraints. Change only the approved architecture document; do not design the solution, review a plan, audit implementation, edit product code, or invent missing targets.

Execution contract: The ordered checkboxes are the Definition of Done. Track every item internally as PENDING, PROVEN with concrete evidence, CLEARED with evidence that its condition is absent, or UNPROVEN with a gap; reading, delegation, or tool failure is not proof. Reconcile items after each section. Before returning, resolve all PENDING and count only PROVEN and CLEARED; apply the skill's verdict and approval rules to every gap. Preserve user intent, scope, and existing authorization. Continue authorized work; ask only for consequential unresolved choices or required external approval. Scale depth to material risk without silently skipping checks. Preserve dependency and safety ordering; otherwise choose the verification method appropriate to each obligation.

Tool Routing

NeedPreferred capabilityFallback
Repository rules and document conventionsNative file reads plus focused searchUser-provided convention with an explicit limitation
Existing requirements and architecture artifactsNarrow repository search and direct readsConversation evidence marked with its source
Current workload or service evidenceMetrics, dashboards, logs, manifests, or checked-in reportsMark UNKNOWN; never manufacture production numbers
Current external limits or standardsOfficial documentation or specificationsMark the claim UNVERIFIED
Document mutationMinimal patch to the approved Markdown artifactReturn BLOCKED if no safe writable path is authorized

Use external research only when a time-sensitive fact changes a constraint. Do not browse for values that must come from product owners, operators, the repository, or measured workload.

Artifact Rules

  • Prefer an existing unambiguous architecture-requirements document.
  • Otherwise use docs/architecture/system-design-baseline.md.
  • Read before writing, preserve unrelated content, and update facts in place instead of creating parallel truth.
  • Classify applicability separately as APPLICABLE or NOT_APPLICABLE, with evidence for exclusions.
  • Rank each applicable item as DRIVER, SUPPORTING, or INFORMATIONAL.
  • Classify evidence separately as CONFIRMED, ASSUMED, or UNKNOWN.
  • Separate observed current values, required targets, hard limits, and future evolution triggers.
  • Express quality attributes through observable scenarios and response measures; record undecided targets as missing decisions rather than inventing numbers.
  • Treat the baseline as versioned project knowledge, not an immutable promise.

Checklist

1. Establish Scope and Destination

  • Resolve the project, business outcome, intended readers, approved documentation scope, and language.
  • Read applicable repository instructions and inspect Git state so unrelated changes remain untouched.
  • Search for existing requirement, architecture, SLO, recovery, security, cost, and ownership documents.
  • Select one canonical artifact: reuse a clear equivalent or choose the default path; explain why no duplicate will be created.
  • Return BLOCKED if the destination is ambiguous and choosing one could split project truth.

2. Build the Evidence Ledger

  • Collect business goals, actors, journeys, scope, non-goals, and decision horizon with their sources and confidence for the driver analysis; do not create a second context inventory.
  • Record sources for current workload, data volume, service behavior, platform limits, and existing commitments.
  • Separate repository facts from stakeholder choices and estimates.
  • Detect contradictions between documents, code, configuration, and stated requirements; preserve both claims until resolved.
  • Ask only for choices whose absence materially changes architecture; mark all other gaps UNKNOWN.

3. Define and Prioritize Architecture Drivers

  • Business and scope: Record actors, critical journeys, business horizon, scope, non-goals, and externally committed outcomes.
  • Demand and data scale: Record current and target users, rates, concurrency, payloads, growth, retention, and forecast horizon where relevant.
  • User-observable service quality: Define SLIs and SLOs for availability, latency, throughput, error rate, correctness, or freshness with measurement windows.
  • Data semantics and recovery: Define consistency, ordering, idempotency, reconciliation, durability, backup, RTO, RPO, and acceptable data loss at affected boundaries.
  • Security, privacy, and compliance: Define trust boundaries, data classification, residency, access, audit, and destructive-action constraints.
  • Operations and economics: Define ownership, operational capacity, cost envelope, supported regions, delivery cadence, and platform or vendor constraints.
  • Evolution: Record thresholds, business events, or evidence that justify revisiting an assumption, target, or deferred capability.
  • Separate applicability, criticality, and evidence status; do not use UNKNOWN to mean unimportant or NOT_APPLICABLE.
  • Prioritize the few scenarios most likely to shape architecture and express each as source/stimulus/environment/artifact/response/measure.

4. Write the Baseline

  • Create or update the artifact with: identity and status; business context; scope and non-goals; critical scenarios; workload and data; quality targets; recovery; consistency; security; cost and operations; constraints; assumptions and unknowns; review triggers.
  • Give material parameters their theme, applicability, criticality, evidence status, value/range, source, owner, as-of date, and review trigger. State shared metadata once with explicit inheritance; use UNKNOWN for missing ownership or values.
  • Keep calculations reproducible and label estimates separately from observed measurements.
  • Link shared architecture artifacts only by repository path or document title; never require a particular workflow or tool.
  • Preserve historical context needed to understand changed requirements instead of silently rewriting prior commitments.

5. Validate and Report

  • Re-read the written artifact and verify that no unknown was converted into a confident fact.
  • Check that targets are measurable, internally consistent, and proportionate to the evidenced business horizon.
  • Check that every architecture-critical gap has an owner or exact next evidence action.
  • Use READY only when the baseline is usable for decisions and no material unknown lacks a safe handling rule; use INCOMPLETE for a useful artifact with consequential open drivers; use BLOCKED when scope, authority, or destination prevents safe creation.

Self-Check

  • Reconcile before returning. Check item-level evidence, requirement coverage, contradictions, scope, verdict, and applicable cleanup. Correct the report or authorized artifacts. Reuse valid evidence; do not automatically rescan the repository or rerun successful commands. Repeat checks only for relevant changes, failures, or unresolved evidence. Disclose remaining gaps.

Output Contract

Report in the user's language, in this order; retain all five fields and state each fact once. Small results may use one line per field; omit empty tables and do not copy linked artifacts:

  1. Result: Skill-specific verdict and supported outcome.
  2. Scope: Reviewed/changed scope, exclusions, baseline, and material assumptions.
  3. Evidence: Skill-specific fields below; distinguish facts, inferences, and unverified claims. Link artifacts; use tables when useful.
  4. Verification: Checks/results, unavailable evidence, and applicable cleanup/external state.
  5. Completion: Checklist: X/Y complete; Incomplete: None or each UNPROVEN item's reason, outcome impact, and exact next action; residual risks and required decisions.

Skill-specific evidence: Artifact path, established drivers and prioritized quality scenarios, applicable constraints, and changed sections. The artifact owns the driver register: theme/parameter, applicability, criticality, evidence status, value/measure, source/owner, as-of date, and review trigger. Summarize only decision-changing gaps; do not copy the register into the response.

Signals

GitHub stars
559
Forks
83
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
ln-71-system-design-baseline-builder
Source
github.com/levnikolaevich/claude-code-skills