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Analyze codebase with parallel mapper agents to produce .planning/codebase/ documents
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Basierend auf der SOC-Berufsklassifikation
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Use this skill when the user wants direct operations on an Obsidian vault: read or edit notes and daily notes, search vault contents, count or list notes, manage tasks, move or rename files, find orphaned notes or broken links, inspect frontmatter/properties, manage sync or file history, query Bases, manage bookmarks, script the CLI, or run JavaScript against the Obsidian API. Trigger when the request implies "go into my vault and do X"; the user wants action on vault data, not an explanation. Skip pure conceptual or GUI-help questions such as settings navigation, theme/plugin installation, sync troubleshooting, Dataview syntax, keyboard shortcuts, or parsing vault files with unrelated external scripts.
Captures corrections, failures, missing capabilities, and reusable discoveries in agent so future work improves. Use this skill whenever a command, tool, or API fails unexpectedly; the user corrects the agent; the agent realizes its knowledge is outdated or wrong; a missing capability is exposed; or a better recurring approach is discovered. Record the result under .agents/learnings/, review related entries before major tasks, and promote durable workflow rules into AGENTS.md when they should change future behavior.
Generate tests for a completed phase based on UAT criteria and implementation
Generate an AI-SPEC.md design contract for phases that involve building AI systems.
Autonomous audit-to-fix pipeline — find issues, classify, fix, test, commit
| name | gsd-map-codebase |
| description | Analyze codebase with parallel mapper agents to produce .planning/codebase/ documents |
Each mapper agent explores a focus area and writes documents directly to .planning/codebase/. The orchestrator only receives confirmations, keeping context usage minimal.
Output: .planning/codebase/ folder with 7 structured documents about the codebase state.
<execution_context> @/home/aming/.config/opencode/gsd-core/workflows/map-codebase.md </execution_context>
- **--fast**: Lightweight scan mode — spawns one mapper agent instead of four. Accepts an optional `--focus` value: `tech`, `arch`, `quality`, `concerns`, or `tech+arch` (default). Faster and lower-context than the full map. - **--query**: Codebase intelligence query mode. Sub-commands: `query `, `status`, `diff`, `refresh`. Requires intel to be enabled in config (`intel.enabled: true`). Runs inline for query/status/diff; spawns an agent for refresh. - **(no flag)**: Full parallel map — spawns 4 mapper agents to produce all 7 codebase documents. Arguments: $ARGUMENTSParse the first token of $ARGUMENTS:
--fast: strip the flag, run the scan workflow (passing remaining args including optional --focus).--query: strip the flag, run the intel workflow (passing remaining args as the subcommand).Load project state if exists: Check for .planning/STATE.md - loads context if project already initialized
This command can run:
<when_to_use> Use map-codebase for:
Skip map-codebase for:
<success_criteria>