# Playbook Domain Schema — Layer 3 Specialized Entity Type # KNO Schema Version: 0.1.0 # CHANGELOG: # 0.1.0 (M52 P4.1, #2139): Add `visibility: public` collection default per REQ-18. # Playbooks are public reference knowledge consumed via the # four-surface contract. # # A playbook is a curated collection of methodological knowledge extracted # from analyzing instruction files, prompts, and documentation across repositories. # # EXTENDS: document-schema.kno (which composes identity, history, quality) # ENABLES: Project scaffolding, methodology application, agent guidance # # DESIGN PRINCIPLE: Playbooks are Generated, Not Authored # - Playbooks are produced by analyzing Corpora via Analysis Jobs # - They link back to their source Corpus for provenance # - Refresh re-analyzes the corpus to update the playbook # # VCS-MANDATORY: Generated playbooks promoted to Hive ARE versioned. # Being "generated" does NOT exempt from VCS recording. # See: kno-foundational-principles.md § VCS-Mandatory Rule # ============================================================================= # SCHEMA DECLARATION (RFC-007) # ============================================================================= $schema: kno@0.0.9 # ============================================================================= # IDENTITY (composed from identity-schema.kno) # ============================================================================= id: 01KGK3V73NCG60MPX3WCVBC2KE slug: playbook-schema type: spec version: 0.6.0 # ============================================================================= # VISIBILITY DECLARATION (REQ-18) — collection default # ============================================================================= # Playbook entities (content/playbooks/*.kno) are public reference knowledge by # default. Per REQ-18, individual entities MAY override with their own # `visibility:` field (last-write-wins at the entity level). Drives the # four-surface contract per kno-system_architecture.md § Agent Surface # Integration and public-surface-parity.instructions.md. visibility: public # ============================================================================= # STANDARD TIER # ============================================================================= title: "Playbook Domain Schema" purpose: | Define the schema for Playbook entities — structured methodology knowledge extracted from corpus analysis. **What is a Playbook?** A playbook encodes: - **Principles**: Foundational beliefs and approaches - **Procedures**: Step-by-step workflows - **Patterns**: Proven solutions with context - **Agent Roles**: How AI assistants should behave - **Quality Gates**: Validation checkpoints **Generation Pipeline:** ``` Corpus ──[Analysis Job]──▶ Dimension Analyses ──[Synthesis]──▶ Playbook ``` **Layer 3 Position**: Playbook extends document (Layer 2), which composes identity, history, and quality (Layer 1). # ============================================================================= # RICH TIER — Relationships (Edge Maximization) # ============================================================================= provenance: origin: id: 01KGK3V73NCG60MPX3WCVBC2KE timestamp: "2026-02-04T01:47:56Z" tool: manual-migration taxonomy: topics: - methodology - instruction-files - agentic-development - knowledge-management keywords: - playbook - methodology - instruction - agent-role - workflow - pattern - principle - quality-gate relationships: extends: - xri: "kno://specs/document-schema" reason: "Layer 2 base type for structured entities" depends_on: - xri: "kno://specs/kno-spec" reason: "RFC-001 defines kno@0.0.9 schema" - xri: "kno://specs/corpus-schema" reason: "Playbooks are generated from corpus analysis" composes: # Inherited through document-schema.kno: - xri: "kno://specs/identity-schema" reason: "Layer 1: id, canonical_id, local_ids, equiv_ids" - xri: "kno://specs/history-schema" reason: "Layer 1: _history, changelog" - xri: "kno://specs/quality-schema" reason: "Layer 1: quality, validation, confidence" enables: - xri: "kno://concepts/project-scaffolding" reason: "Apply playbook to new projects" - xri: "kno://concepts/methodology-evaluation" reason: "Evaluate methodology completeness" implements: - xri: "kno://principles/P9" reason: "Temporal/Historical — generated playbooks are versioned in Hive" - xri: "kno://principles/VCS-Mandatory-Rule" reason: "Playbooks promoted to Hive MUST be recorded in VCS (depth_policy: hybrid)" related_to: - xri: "kno://specs/user-schema" reason: "Users own playbooks" - xri: "kno://specs/organization-schema" reason: "Organizations can own playbooks" - xri: "kno://concepts/analysis-job" reason: "Analysis jobs produce playbooks" quality: status: "reviewed" last_reviewed: "2026-01-25" review_status: draft # ============================================================================= # HISTORY (P9 Temporal — composed from history-schema.kno) # ============================================================================= _history: version: 5 created: "2025-01-18T00:00:00Z" created_by: "pspace-core-team" modified: "2026-02-24T00:00:00Z" modified_by: "claude" # ============================================================================= # SPECIFICATION CONTENT # ============================================================================= spec: status: Draft changelog: - version: "0.5.0" date: "2026-02-24" changes: - "Added dimension_profile as optional top-level object field (#362)" - "Added type_code as optional top-level object field (#363)" - "Added quality.evaluation object for Evaluator Agent output (#364)" - "Schema changes combined into single minor bump (#362, #363, #364)" - version: "0.4.0" date: "2026-02-24" changes: - "Added throughlines as optional top-level array field (#350)" - "Throughline properties: theme, description, entry_refs, dimensions" - "entry_refs requires ≥3 entries, dimensions requires ≥2 dimension keys" - "Added throughlines to Full Playbook example" - version: "0.3.0" date: "2026-02-24" changes: - "Added beliefs as optional top-level array field (#349)" - "Belief properties: statement, evidence, dimensions, distinctiveness" - "Distinctiveness enum: unique | uncommon | common" - "Added beliefs to Full Playbook example" - version: "0.2.0" date: "2026-02-21" changes: - "Added VCS-Mandatory Rule documentation and cross-references" - "Added depth_policy field to schema (recommended: hybrid, default retention: 10)" - "Added implements relationship for P9 and VCS-Mandatory-Rule" - "Clarified that generated playbooks promoted to Hive are versioned" - version: "0.1.0" date: "2026-01-25" changes: - "Promoted from holding-pen to specs/" - "Updated to kno@0.0.9 schema format" - "Aligned with bedrock principles (no facets, edge inference)" - "Added Layer 3 positioning in relationships" - "Linked to corpus-schema via depends_on" - "Simplified domain taxonomy to strings (edge inference)" description: | ## Generation Pipeline Playbooks are not authored directly — they are generated through analysis. > **VCS-Mandatory Rule:** Although playbooks are generated (not authored), > they are promoted to the Hive and therefore MUST be recorded in a > compliant VCS backend. The recommended `depth_policy` is `hybrid:10`. > Being "generated" does NOT exempt an entity from versioning — only > ephemeral scratch entities that never reach Hive use `none`. > See: kno-foundational-principles.md § VCS-Mandatory Rule ``` ┌─────────────────────────────────────────────────────────────────────────┐ │ PLAYBOOK GENERATION PIPELINE │ ├─────────────────────────────────────────────────────────────────────────┤ │ │ │ ┌──────────┐ ┌──────────────┐ ┌──────────────┐ │ │ │ Corpus │ ───▶ │ Analysis Job │ ───▶ │ Dimension │ │ │ │ (input) │ │ (process) │ │ Analyses │ │ │ └──────────┘ └──────────────┘ └───────┬──────┘ │ │ │ │ │ ▼ │ │ ┌──────────────┐ │ │ │ Synthesis │ │ │ │ (combine) │ │ │ └───────┬──────┘ │ │ │ │ │ ▼ │ │ ┌──────────────┐ │ │ │ Playbook │ │ │ │ (output) │ │ │ └──────────────┘ │ │ │ └─────────────────────────────────────────────────────────────────────────┘ ``` ## Domain Taxonomy Playbooks organize content into these domains (discovered from source repos): | Category | Domain | Description | |----------|--------|-------------| | Methodology | `methodology.project_management` | Work hierarchy, MMF, task sizing | | Methodology | `methodology.agentic_development` | Agent roles, assignment, handoffs | | Methodology | `methodology.decision_frameworks` | Strategic and architectural decisions | | Technical | `technical.architecture` | Design patterns, API design | | Technical | `technical.development` | Coding standards, naming | | Technical | `technical.testing` | TDD, integration, E2E | | Technical | `technical.infrastructure` | CI/CD, containers, observability | | Process | `process.governance` | Quality gates, validation | | Process | `process.github_integration` | Issues, projects, automation | | Process | `process.documentation` | Instruction files, wikis | | Culture | `culture.communication` | Collaboration, AI style | | Culture | `culture.philosophy` | Agent-first design, principles | ## Content Types | Type | Description | Example | |------|-------------|---------| | `principle` | Foundational beliefs | "Agent-first design" | | `procedure` | Step-by-step workflows | "Task creation workflow" | | `rule` | Hard constraints | "All PRs require review" | | `pattern` | Proven solutions | "Repository structure pattern" | | `anti_pattern` | What to avoid | "Monolithic instruction files" | | `template` | Reusable structures | "Epic template" | | `reference` | Quick lookup | "Git commit conventions" | # =========================================================================== # SCHEMA # =========================================================================== schema: type: object required: - id - type - version - name - corpus_id - domains properties: # ----------------------------------------------------------------------- # BASIC TIER (from kno-spec) # ----------------------------------------------------------------------- id: type: string pattern: "^playbook_[a-zA-Z0-9]+$" description: | Unique identifier for this playbook. Convention: playbook_{ulid} examples: - "playbook_01HXYZ123" - "playbook_01AWECELOT" type: const: playbook description: "Always 'playbook' for this schema" version: type: string pattern: "^\\d+\\.\\d+\\.\\d+$" description: "Version of this playbook entity" default: "0.1.0" # ----------------------------------------------------------------------- # STANDARD TIER # ----------------------------------------------------------------------- name: type: string pattern: "^[a-z][a-z0-9-]*$" description: "Lowercase, hyphenated name for this playbook" examples: - "awecelot" - "howl-methodology" title: type: string description: "Human-readable title" examples: - "Awecelot Solopreneur Methodology" description: type: string description: "What this playbook encodes and its purpose" purpose: type: string description: "One-line statement of playbook's purpose" # ----------------------------------------------------------------------- # RICH TIER (from kno-spec via document-schema composition) # ----------------------------------------------------------------------- taxonomy: type: object description: "P5 Contextual Richness — topics and keywords" properties: topics: type: array items: type: string description: "Domain topics covered" keywords: type: array items: type: string description: "Searchable keywords" relationships: type: object description: "REQ-07 Explicit relationships with XRI addresses" properties: conforms_to: type: array items: type: object properties: xri: type: string reason: type: string derived_from: type: array items: type: object properties: xri: type: string reason: type: string enables: type: array items: type: object properties: xri: type: string reason: type: string related_to: type: array items: type: object properties: xri: type: string reason: type: string quality: type: object description: "P8 Trust Verification — content quality metadata" properties: status: type: string description: "Qualitative label: synthesized-draft, evaluated, reviewed, approved" completeness: type: number description: "DEPRECATED — legacy numeric score (0.0-1.0). Use status instead. See #343." deprecated: true evaluation: type: object description: | Structured evaluation from the Evaluator Agent (#361). Five-axis quality assessment from the perspective of an entrepreneur choosing between playbooks. properties: evaluator: type: string description: "Evaluator persona identifier" examples: - "entrepreneur-v1" evaluated_at: type: string format: date-time description: "When the evaluation was performed" axes: type: object description: "Five evaluation axes, each with score and rationale" properties: actionability: type: object properties: score: type: number minimum: 0 maximum: 1 description: "0-1 score for actionability" rationale: type: string description: "One-sentence explanation" specificity: type: object properties: score: type: number minimum: 0 maximum: 1 rationale: type: string coherence: type: object properties: score: type: number minimum: 0 maximum: 1 rationale: type: string completeness: type: object properties: score: type: number minimum: 0 maximum: 1 rationale: type: string trust: type: object properties: score: type: number minimum: 0 maximum: 1 rationale: type: string summary: type: string description: "Overall evaluation summary" distinctive_quality: type: string description: "What makes this playbook special" last_reviewed: type: string format: date-time review_status: type: string description: "needs-review, reviewed, approved" reviewed_by: type: string description: "XRI of reviewer" _history: type: object description: "P9 Temporal Awareness — creation and modification tracking" properties: version: type: string created: type: string format: date-time created_by: type: string description: "XRI of creator" modified: type: string format: date-time modified_by: type: string description: "XRI of modifier" # ----------------------------------------------------------------------- # CORPUS LINKAGE (Timeless Model) # ----------------------------------------------------------------------- corpus_id: type: string description: | Reference to the Corpus entity this playbook was generated from. Part of the timeless model: corpus defines sources, playbook is the analysis output. examples: - "corpus_01HOWL456" - "corpus_01COMBINED" job_id: type: string description: "Analysis job that generated this playbook" examples: - "job_01ANALYSIS123" # ----------------------------------------------------------------------- # DOMAIN COVERAGE # ----------------------------------------------------------------------- domains: type: array items: type: string description: "What methodology domains this playbook covers" examples: - "methodology.project_management" - "methodology.agentic_development" - "technical.architecture" - "process.governance" # ----------------------------------------------------------------------- # AGENT ROLES # ----------------------------------------------------------------------- agent_roles: type: array description: "Agent role definitions for this methodology" items: type: object required: - id - name properties: id: type: string pattern: "^[a-z_]+$" examples: - "project_manager" - "pair_programmer" name: type: string examples: - "Project Manager (PM)" responsibilities: type: array items: type: string description: "What this role does" autonomy_level: type: string description: "Level of autonomous action" examples: - "propose" - "apply" - "review" outputs: type: array items: type: string description: "What this role produces" when_to_engage: type: array items: type: string description: "Triggers for engaging this role" # ----------------------------------------------------------------------- # CONTENT ENTRIES # ----------------------------------------------------------------------- entries: type: array description: "Knowledge entries in this playbook" items: type: object required: - id - type - title - domain properties: id: type: string description: "Entry identifier" type: type: string description: "Content type" examples: - "principle" - "procedure" - "rule" - "pattern" - "anti_pattern" - "template" - "reference" title: type: string description: "Human-readable title" domain: type: string description: "Domain path (e.g., 'methodology.project_management')" content: type: string description: "Markdown content" source_file: type: string description: "Original instruction file path" priority: type: string description: "Importance level" examples: - "P0" - "P1" - "P2" tags: type: array items: type: string related: type: array items: type: string description: "Related entry IDs" # ----------------------------------------------------------------------- # WORKFLOWS # ----------------------------------------------------------------------- workflows: type: array description: "Process workflows defined by this playbook" items: type: object required: - id - name - stages properties: id: type: string name: type: string description: type: string trigger: type: string description: "What starts this workflow" stages: type: array items: type: object properties: id: type: string name: type: string responsible: type: string description: "Agent role ID" outputs: type: array items: type: string # ----------------------------------------------------------------------- # QUALITY GATES # ----------------------------------------------------------------------- quality_gates: type: array description: "Validation checkpoints" items: type: object required: - id - name - checklist properties: id: type: string name: type: string applies_at: type: string description: "When to apply this gate" examples: - "pre_task" - "post_task" - "pre_release" checklist: type: array items: type: string description: "Checklist items" # ----------------------------------------------------------------------- # BELIEFS (#349) # ----------------------------------------------------------------------- beliefs: type: array description: | Core belief statements that distinguish this methodology. Beliefs are explicit value statements extracted from playbook entries, backed by evidence chains and classified by distinctiveness. Derived from S3 entity `belief` fields and cross-entry synthesis. Target: 3-8 beliefs per playbook. Omit if no meaningful beliefs found. items: type: object required: - statement - evidence properties: statement: type: string description: | The belief in one sentence — concise, assertive, falsifiable. Must be specific to THIS methodology, not a generic truism. examples: - "AI agents should operate with zero memory dependency between sessions" - "Every task must be the smallest atomic unit that delivers user value" evidence: type: array description: "Entry IDs that support this belief (≥2 required)" items: type: string examples: - [ "agent-first-design", "zero-memory-principle", "tool-integration", ] dimensions: type: array description: "Which dimensions this belief spans (e.g., 'D1', 'D3', 'D7')" items: type: string examples: - ["D1", "D3", "D7"] distinctiveness: type: string enum: - unique - uncommon - common description: | How distinctive this belief is across playbooks. - unique: Unlikely to appear in other methodologies - uncommon: Appears in some but with different emphasis - common: Widely held but included for completeness # ----------------------------------------------------------------------- # THROUGHLINES (#350) # ----------------------------------------------------------------------- throughlines: type: array description: | Cross-cutting themes that weave through multiple entries and dimensions. Throughlines are the connective tissue of the playbook — recurring ideas that transcend individual entries and form coherent threads through the methodology. A throughline is identified when 3+ entries across 2+ dimensions reference the same core concept. Target: 2-6 throughlines per playbook. Omit if none found. items: type: object required: - theme - entry_refs - dimensions properties: theme: type: string description: "Short name for the throughline" examples: - "Agent autonomy with guardrails" - "Incremental delivery" description: type: string description: | What this throughline means in the context of this methodology and why it matters. entry_refs: type: array description: "Entry IDs that participate in this throughline (≥3 required)" items: type: string examples: - [ "agent-first-design", "autonomy-levels", "quality-gates", "pair-programming", ] dimensions: type: array description: "Which dimensions this throughline spans (≥2 required, as DimensionKey strings)" items: type: string examples: - ["D1", "D3", "D5"] # ----------------------------------------------------------------------- # DIMENSION PROFILE (#362) # ----------------------------------------------------------------------- dimension_profile: type: object description: | Pre-computed dimension distribution across playbook entries. Generated by the S4 assembly step. When present, the UI uses these values directly instead of re-computing from per-entry dimension arrays. properties: D1: type: object properties: count: { type: integer, description: "Number of entries tagged with D1", } weight: { type: number, description: "Normalized weight (0-1)" } D2: type: object properties: count: { type: integer } weight: { type: number } D3: type: object properties: count: { type: integer } weight: { type: number } D4: type: object properties: count: { type: integer } weight: { type: number } D5: type: object properties: count: { type: integer } weight: { type: number } D6: type: object properties: count: { type: integer } weight: { type: number } D7: type: object properties: count: { type: integer } weight: { type: number } D8: type: object properties: count: { type: integer } weight: { type: number } D9: type: object properties: count: { type: integer } weight: { type: number } D10: type: object properties: count: { type: integer } weight: { type: number } dominant: type: array items: type: string description: "Top dimensions by weight (e.g., 'D1', 'D3')" sparse: type: array items: type: string description: "Bottom dimensions by weight — blind spots" # ----------------------------------------------------------------------- # TYPE CODE (#363) # ----------------------------------------------------------------------- type_code: type: object description: | Pre-computed playbook type code along five axes. Generated by the S4 assembly step. When present, the UI uses these values instead of computing client-side via computeTypeCode(). properties: code: type: string description: "Compact type code string" examples: - "Φ-E-A-R-X" - "P-Pr-S-Pr-I" label: type: string description: "Human-readable label describing the playbook character" examples: - "Philosophical engineer — self-directed" - "Prescriptive product lead — supervised" axes: type: object description: "Individual axis values with continuous ratios" properties: prescriptive_philosophical: type: object properties: letter: { type: string, description: "Axis code letter (P or Φ)" } label: { type: string, description: "Human-readable axis position", } value: { type: number, minimum: 0, maximum: 1, description: "Continuous ratio (0=prescriptive, 1=philosophical)", } engineering_product: type: object properties: letter: { type: string } label: { type: string } value: { type: number, minimum: 0, maximum: 1, description: "0=product, 1=engineering", } autonomous_supervised: type: object properties: letter: { type: string } label: { type: string } value: { type: number, minimum: 0, maximum: 1, description: "0=supervised, 1=autonomous", } retrospective_prospective: type: object properties: letter: { type: string } label: { type: string } value: { type: number, minimum: 0, maximum: 1, description: "0=prospective, 1=retrospective", } explicit_implicit: type: object properties: letter: { type: string } label: { type: string } value: { type: number, minimum: 0, maximum: 1, description: "0=implicit, 1=explicit", } # ----------------------------------------------------------------------- # PROVENANCE # ----------------------------------------------------------------------- provenance: type: object description: "Where this playbook's knowledge came from" properties: source_repos: type: array items: type: object properties: repo: type: string commit: type: string paths: type: array items: type: string generated_at: type: string format: date-time generated_by: type: string description: "User or system that generated this playbook" model: type: string description: "LLM model used for analysis" examples: - "claude-opus-4-20250514" # ----------------------------------------------------------------------- # HISTORY POLICY (VCS-Mandatory Rule) # ----------------------------------------------------------------------- depth_policy: type: string enum: - full - hybrid - changelog - external default: hybrid description: | History retention policy for this playbook. Composed from history-schema.kno. NOTE: `none` is intentionally excluded. Playbooks are promoted to the Hive, so VCS recording is mandatory per the VCS-Mandatory Rule. Generated entities that reach Hive cannot use `none`. Recommended: `hybrid` with default retention of 10 versions. This balances portability (recent history travels with the entity) and completeness (all versions in VCS backend). retention: type: integer minimum: 1 default: 10 description: | For 'hybrid' policy: number of versions to keep embedded in the .kno container. Older versions are stored only in the VCS backend. Default: 10. # ----------------------------------------------------------------------- # STORAGE & METADATA # ----------------------------------------------------------------------- storage_uri: type: string description: "MinIO URI for playbook files" examples: - "pspace-storage:///hive/playbooks/playbook_01HXYZ123/" owner_id: type: string description: "User ID who owns this playbook" visibility: type: string description: "Access control" examples: - "private" - "organization" - "public" status: type: string description: "Playbook lifecycle status" examples: - "generating" - "ready" - "archived" tags: type: array items: type: string description: "Optional tags for filtering" # ============================================================================= # EXAMPLES # ============================================================================= examples: - name: "Minimal Playbook" description: "Simplest valid playbook" value: $schema: "kno://specs/playbook-schema@0.1" id: "playbook_01MINIMAL" type: "playbook" version: "0.1.0" name: "example" corpus_id: "corpus_01HXYZ123" domains: - "methodology.project_management" entries: - id: "mmf-principle" type: "principle" title: "Minimally Marketable Features" domain: "methodology.project_management" content: | Every task should deliver the smallest atomic unit of functionality that provides user value. status: "ready" - name: "Full Playbook" description: "Playbook with all sections including RICH tier" value: $schema: "kno://specs/playbook-schema@0.1" id: "playbook_01AWECELOT" type: "playbook" version: "0.1.0" name: "awecelot" title: "Awecelot Solopreneur Methodology" description: | A methodology for solo developers working with AI agents, derived from analyzing Howl and Pongogo repositories. purpose: "Operational playbook for solopreneur AI-assisted development" # RICH tier: Taxonomy (P5) taxonomy: topics: - "methodology.project_management" - "methodology.agentic_development" - "technical.architecture" keywords: - "agent-first" - "MMF" - "solopreneur" # RICH tier: Relationships (REQ-07) relationships: derived_from: - xri: "pspace://corpus:corpus_01COMBINED" reason: "Source corpus for playbook extraction" conforms_to: - xri: "kno://specs/playbook-schema@0.1" reason: "Schema conformance" related_to: - xri: "pspace://synthesis-job/job_01ANALYSIS789" reason: "Synthesis job that generated this playbook" # RICH tier: Quality (P8) quality: status: "evaluated" last_reviewed: "2026-01-25T10:00:00Z" review_status: "needs-review" evaluation: evaluator: "entrepreneur-v1" evaluated_at: "2026-02-24T12:00:00Z" axes: actionability: score: 0.7 rationale: "Good ratio of procedures and templates to principles" specificity: score: 0.9 rationale: "Highly specific to solopreneur AI-assisted development" coherence: score: 0.8 rationale: "Consistent agent-first worldview across all entries" completeness: score: 0.6 rationale: "Missing coverage in D6 (testing) and D8 (infrastructure)" trust: score: 0.5 rationale: "Two source repos provide moderate evidence density" summary: "Strong methodology with excellent specificity but gaps in operational coverage" distinctive_quality: "The agent-first design philosophy creates a uniquely autonomous development workflow" # Temporal tracking (P9) _history: version: "0.1.0" created: "2026-01-25T10:00:00Z" created_by: "pspace://agent:synthesis-pipeline" modified: "2026-01-25T10:00:00Z" modified_by: "pspace://agent:synthesis-pipeline" corpus_id: "corpus_01COMBINED" job_id: "job_01ANALYSIS789" domains: - "methodology.project_management" - "methodology.agentic_development" - "technical.architecture" - "process.governance" - "culture.philosophy" agent_roles: - id: "project_manager" name: "Project Manager (PM)" responsibilities: - "Epic planning and task breakdown" - "Progress tracking and coordination" autonomy_level: "propose" outputs: - "Epic structures" - "Status reports" when_to_engage: - "Creating new epics" - "Planning milestones" - id: "pair_programmer" name: "Pair Programmer" responsibilities: - "Code implementation" - "Unit testing" autonomy_level: "apply" outputs: - "Working code" - "Tests" entries: - id: "agent-first-design" type: "principle" title: "Agent-First Design" domain: "culture.philosophy" priority: "P0" content: | Build systems for AI consumption first, human second. - Automatic discovery - Built-in tool integration - Zero memory dependency tags: - "foundational" - "philosophy" workflows: - id: "task-creation" name: "Task Creation Workflow" trigger: "New work identified" stages: - id: "research" name: "Research Phase" responsible: "project_manager" outputs: - "Existing work search" - id: "decision" name: "Decision Phase" responsible: "project_manager" outputs: - "Task vs Epic decision" quality_gates: - id: "pre-task" name: "Pre-Task Quality Gate" applies_at: "pre_task" checklist: - "MMF compliance verified" - "Agent assignable confirmed" - "Domain bounded verified" beliefs: - statement: "AI agents should operate with zero memory dependency between sessions" evidence: - "agent-first-design" dimensions: - "D1" - "D5" distinctiveness: "unique" - statement: "Every task must be the smallest atomic unit that delivers user value" evidence: - "agent-first-design" dimensions: - "D3" - "D4" distinctiveness: "uncommon" throughlines: - theme: "Agent autonomy with guardrails" description: "Agents are given meaningful autonomy but within structured quality gates and review checkpoints" entry_refs: - "agent-first-design" dimensions: - "D1" - "D3" - "D5" dimension_profile: D1: { count: 5, weight: 0.22 } D2: { count: 3, weight: 0.13 } D3: { count: 4, weight: 0.17 } D4: { count: 2, weight: 0.09 } D5: { count: 3, weight: 0.13 } D6: { count: 1, weight: 0.04 } D7: { count: 2, weight: 0.09 } D8: { count: 1, weight: 0.04 } D9: { count: 1, weight: 0.04 } D10: { count: 1, weight: 0.04 } dominant: - "D1" - "D3" sparse: - "D6" - "D8" type_code: code: "Φ-E-A-R-X" label: "Philosophical engineer — self-directed" axes: prescriptive_philosophical: letter: "Φ" label: "Philosophical" value: 0.65 engineering_product: letter: "E" label: "Engineering" value: 0.72 autonomous_supervised: letter: "A" label: "Autonomous" value: 0.80 retrospective_prospective: letter: "R" label: "Retrospective" value: 0.55 explicit_implicit: letter: "X" label: "Explicit" value: 0.45 provenance: source_repos: - repo: "howl-app/howl" commit: "dbebd0f" paths: - ".github/instructions/" - repo: "pongogo/pongogo" commit: "1c69e5c" paths: - "knowledge/instructions/" generated_at: "2026-01-25T10:00:00Z" generated_by: "pspace://user:usr_01ADMIN" model: "claude-opus-4-20250514" storage_uri: "pspace-storage:///hive/playbooks/playbook_01AWECELOT/" owner_id: "usr_01ADMIN" visibility: "private" status: "ready" tags: - "methodology" - "solopreneur"