version: "1.0.1" name: knowledge-build description: "Orchestrates parallel KB generation using spatial analysis and a map-reduce architecture with incremental and feature-learning modes." allowed-tools: Bash(echo ), Bash(rp1 ), Bash(git ), Bash(jq ), Bash(wc ), Bash(mkdir ) metadata: category: knowledge is_workflow: true arcade_tracked: false workflow: run_policy: fresh identity_args: [] version: 2.2.1 tags:

• documentation
• analysis
• planning
• core
• parallel

created: 2025-10-25 updated: 2026-04-09 author: cloud-on-prem/rp1 arguments:

• name: FEATURE_ID

type: string required: false description: "Feature ID to incorporate learnings from an archived or active feature into KB" sub_agents:

• "rp1-base:kb-spatial-analyzer"
• "rp1-base:kb-concept-extractor"
• "rp1-base:kb-architecture-mapper"
• "rp1-base:kb-interaction-mapper"
• "rp1-base:kb-module-analyzer"
• "rp1-base:kb-pattern-extractor"

Knowledge Build

§ROLE: KB orchestrator. Update kbRoot, not workRoot.

§CTX

• Use the pre-resolved projectRoot, kbRoot, and workRoot values from the generated Workflow Bootstrap section.
• KB outputs live under kbRoot:
• index.md
• concept_map.md
• architecture.md
• interaction-model.md
• modules.md
• patterns.md
• state.json
• meta.json
• index.md is orchestrator-owned. Never delegate it.
• state.json is shareable. meta.json is local-only and SHOULD be gitignored.
• Exclude these paths from change scope and file hygiene:
• node_modules/, .git/, build/, dist/, cli/dist/, target/, .next/, __pycache__/, vendor/, .venv/, .rp1/context/

§DO

• Execute immediately. No approval loop.
• Single pass. No refinement loop.
• Treat this as an orchestrator, not a wrapper.
• FULL means wide evidence collection, not blank-slate regeneration.
• When prior KB exists, section agents MUST reconcile against it, even in FULL.
• Section agents MUST also treat prior KB as incomplete and perform one explicit novelty scan for material knowledge absent from it.
• Replace all placeholders with concrete values before dispatching child agents.
• Spawn the 5 analysis agents in one parallel batch.
• Wait patiently for child agents on the critical path. Do not declare them stalled after a short wait.
• Keep user-visible output terse:

1. Initial status line
2. Sparse progress only when useful
3. Final report or fatal error

§PROC

1. Detect Mode

1. Use the pre-resolved directories. Create kbRoot if missing.
2. If FEATURE_ID is non-empty:

• Set MODE=FEATURE_LEARNING.
• Search, in order:
• {workRoot}/archives/features/{FEATURE_ID}
• {workRoot}/features/{FEATURE_ID}
• If neither exists: report the checked paths, stop.
• Read:
• requirements.md
• design.md
• field-notes.md if present
• tasks.md
• Extract FILES_MODIFIED from tasks.md implementation summaries.

Accept patterns like **Files**: and **Files Modified**:.

• If FILES_MODIFIED is empty: explain that feature learning needs a concrete file scope, stop.
• Build FEATURE_CONTEXT with:
• feature id
• feature path
• summarized requirements
• architectural decisions
• discoveries from field notes
• implementation patterns
• files_modified
• Set:
• FILE_SCOPE=FILES_MODIFIED
• FILE_DIFFS={}
• INITIAL_MESSAGE=Feature learning build for {FEATURE_ID}

1. Else use git-driven mode:

• Read {kbRoot}/state.json if it exists.
• Get CURRENT_COMMIT via git rev-parse HEAD.
• If no state.json:
• Set MODE=FULL
• FILE_SCOPE=[]
• FILE_DIFFS={}
• INITIAL_MESSAGE=First-time KB generation with parallel analysis (10-15 min)
• Else read:
• OLD_COMMIT=state.json.git_commit
• REPO_TYPE=state.json.repo_type // "single-project"
• repo_root + current_project_path from {kbRoot}/meta.json
• Fallback: use state.json for those local fields only if meta.json is absent
• If OLD_COMMIT == CURRENT_COMMIT:
• Output KB is up-to-date (commit {CURRENT_COMMIT}). No regeneration needed. and stop
• Build scoped changed-file list:
• If REPO_TYPE=monorepo, run diff from repo_root and filter to current_project_path unless it is . or empty
• Else diff the current repo normally
• Drop excluded paths and obviously irrelevant binary/media files
• If scoped change list is empty:
• Update only git_commit in state.json
• Keep all other fields unchanged
• Output No in-scope changes. Updated commit reference ({OLD_COMMIT} -> {CURRENT_COMMIT}). and stop
• Preserve the full scoped changed-file list as the evidence frontier in both FULL and INCREMENTAL.
• Count changed files:
• > 50 -> MODE=FULL
• <= 50 -> MODE=INCREMENTAL
• If MODE=FULL:
• INITIAL_MESSAGE=Large change set ({N} files). Wide reconcile (10-15 min)
• FILE_SCOPE=<scoped changed files>
• Build FILE_DIFFS as path -> git diff OLD_COMMIT CURRENT_COMMIT -- path
• If MODE=INCREMENTAL:
• INITIAL_MESSAGE=Changes detected since last build ({OLD_COMMIT} -> {CURRENT_COMMIT}). Analyzing {N} changed files (2-5 min)
• FILE_SCOPE=<scoped changed files>
• Build FILE_DIFFS as path -> git diff OLD_COMMIT CURRENT_COMMIT -- path

1. Print INITIAL_MESSAGE.

2. Spatial Analysis

1. Spawn the spatial analyzer with the actual mode and changed-file frontier:

{% dispatch_agent "rp1-base:kb-spatial-analyzer" %} Use the computed build inputs from the parent orchestrator.

• MODE: actual build mode (FULL, INCREMENTAL, or FEATURE_LEARNING)
• CHANGED_FILES: actual JSON array for the scoped changed-file list when available; empty only for first-time FULL
• Task: rank files 0-5 and categorize them into index_files, concept_files, arch_files, interaction_files, module_files
• Return JSON only with:
• repo_type
• monorepo_projects
• total_files_scanned
• index_files
• concept_files
• arch_files
• interaction_files
• module_files
• local_meta

Do not echo placeholder tokens. {% enddispatch_agent %}

1. Parse and validate the JSON.
2. Fatal if:

• JSON missing
• required keys missing
• all file categories empty

1. Store:

• repo_type
• monorepo_projects
• local_meta.repo_root
• local_meta.current_project_path

3. Parallel Analysis

1. Compute:

• PATTERN_FILES = unique(concept_files + module_files)
• INTERACTION_FILES = unique(interaction_files)
• per-agent diff subsets from FILE_DIFFS

1. Spawn all 5 analyzers in one batch:

{% dispatch_agent "rp1-base:kb-concept-extractor", background %} Use the parent-computed inputs.

• KB_ROOT={kbRoot}
• MODE: actual mode
• REPO_TYPE: actual repo type
• CONCEPT_FILES_JSON: actual JSON array
• FILE_DIFFS: actual diff subset JSON or empty object
• FEATURE_CONTEXT: actual feature context JSON or empty object
• Task: return JSON only for concept_map.md

{% enddispatch_agent %}

{% dispatch_agent "rp1-base:kb-architecture-mapper", background %} Use the parent-computed inputs.

• KB_ROOT={kbRoot}
• MODE: actual mode
• REPO_TYPE: actual repo type
• ARCH_FILES_JSON: actual JSON array
• FILE_DIFFS: actual diff subset JSON or empty object
• FEATURE_CONTEXT: actual feature context JSON or empty object
• Task: return JSON only for architecture.md

{% enddispatch_agent %}

{% dispatch_agent "rp1-base:kb-interaction-mapper", background %} Use the parent-computed inputs.

• KB_ROOT={kbRoot}
• MODE: actual mode
• REPO_TYPE: actual repo type
• INTERACTION_FILES_JSON: actual JSON array
• FILE_DIFFS: actual diff subset JSON or empty object
• FEATURE_CONTEXT: actual feature context JSON or empty object
• Task: return JSON only for interaction-model.md

{% enddispatch_agent %}

{% dispatch_agent "rp1-base:kb-module-analyzer", background %} Use the parent-computed inputs.

• KB_ROOT={kbRoot}
• MODE: actual mode
• REPO_TYPE: actual repo type
• MODULE_FILES_JSON: actual JSON array
• FILE_DIFFS: actual diff subset JSON or empty object
• FEATURE_CONTEXT: actual feature context JSON or empty object
• Task: return JSON only for modules.md

{% enddispatch_agent %}

{% dispatch_agent "rp1-base:kb-pattern-extractor", background %} Use the parent-computed inputs.

• KB_ROOT={kbRoot}
• MODE: actual mode
• REPO_TYPE: actual repo type
• PATTERN_FILES_JSON: actual JSON array
• FILE_DIFFS: actual diff subset JSON or empty object
• FEATURE_CONTEXT: actual feature context JSON or empty object
• Task: return JSON only for patterns.md
• Constraint: rendered patterns.md MUST stay <=150 lines

{% enddispatch_agent %}

1. Wait for all 5 agents to finish.
2. Parse JSON from each response.
3. Failure policy:

• 0 failures: continue normally
• 1 failure: continue, but generate a placeholder section for the failed file and report partial success
• 2+ failures: do not write partial KB, stop

4. Reduce + Write

1. Read needed KB templates directly from plugins/base/skills/artifact-templates/templates/knowledge-base/ (fall back to rp1-base:artifact-templates SKILL.md index if a direct path fails).
2. Merge analyzer output into:

• concept_map.md
• architecture.md
• interaction-model.md
• modules.md
• patterns.md

1. Validate the architecture.md Mermaid diagram via rp1-base:mermaid.

• If invalid: simplify or omit the broken diagram, do not fail the whole run for diagram syntax alone.

1. Write these files first:

• {kbRoot}/concept_map.md
• {kbRoot}/architecture.md
• {kbRoot}/interaction-model.md
• {kbRoot}/modules.md
• {kbRoot}/patterns.md

1. Count lines for the written markdown files.
2. Generate index.md directly from aggregated results plus measured line counts.
3. Write {kbRoot}/index.md last.
4. Write {kbRoot}/state.json with:

• strategy=parallel-map-reduce
• repo_type
• monorepo_projects
• generated_at
• git_commit
• files_analyzed
• languages
• metrics

1. Write {kbRoot}/meta.json with:

• repo_root
• current_project_path

1. meta.json is local-only. Write it, but do not register it anywhere.

§FAIL

Fatal errors:

• missing feature path
• empty FILES_MODIFIED in feature mode
• git failure during git-driven mode
• spatial analyzer failure or invalid JSON
• template load failure
• repeated write failure
• 2+ analyzer failures

On any fatal error:

• output a concise message naming the failed phase + cause
• stop immediately

§OUT

User-visible output only:

• Initial mode/status line
• Optional high-level progress line when the run is long
• Final report

Final report must include:

• overall result:
• Knowledge Base Generated Successfully
• Feature Learnings Captured
• or Partial KB Generated
• repository type
• files analyzed
• files written under .rp1/context/
• note that this passive workflow does not register an Arcade run
• reminder: agents load KB automatically via progressive disclosure