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large-workspace-handling

Rosetta skill to partition large workspaces or folders (100+ files recursively) into scoped subagent tasks when single-agent context is insufficient.

40

Quality

40%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./instructions/r2/core/skills/large-workspace-handling/SKILL.md
SKILL.md
Quality
Evals
Security

<large_workspace_handling>

<role>

Workspace partitioning strategist. Draws scope boundaries, dispatches subagents.

</role>

<when_to_use_skill> Use when large workspaces exceed single-agent context window. Partitions into write-scopes where every file belongs to exactly one scope, and merged results address the original request completely. </when_to_use_skill>

<core_concepts>

  • All Rosetta prep steps MUST be FULLY completed, load-context skill loaded and fully executed
  • If CODEMAP.md missing, ACQUIRE init-workspace-discovery/SKILL.md FROM KB and EXECUTE to create ONLY CODEMAP.md
  • Grep # headers of CODEMAP before scoping

Two strategies (mutually exclusive):

  • Summarize & Index
  • Work distribution

Summarization & Indexing

  • Research without changing code, navigable index with module summaries, etc.
  • Assign subagents: scope paths, goal, context, inputs, output format, boundaries, constraints, and level of detail
  • Subagents to ACQUIRE reverse-engineering/SKILL.md FROM KB if needed for code analysis
  • Request slightly more information than actually needed for better understanding
  • Summarize all outputs
  • Subagent: discoverer, explore, etc.
  • Subagent output structure: analysis scope, TLDR answer, quick navigation with relevance, details with subsections per each logical group (globs, purpose, key components, relevant findings, dependencies), cross-group map, follow ups required
  • Subagents to use relevance classification:
    • High: group directly addresses the research question
    • Medium: group has supporting information or context
    • Low: group tangentially related, included for completeness

Work distribution

  • Coordinated modifications via contract-scoped parallel subagents with explicit boundaries and success criteria
  • Split work across subagents and provide: scope paths, goal, context, inputs, output format, boundaries, constraints, operations, and success criteria
  • Subagents decide and execute work within declared scope
  • Resolve cross-scope deps via execution ordering
  • Resolve shared-interface conflicts or changes with extra pass
  • Produce unified result
  • Subagent: executor, engineer, etc.

Task type detection:

  • Summarize & Index keywords: understand, analyze, investigate, explore, document, explain, find, search, review, audit, learn, overview
  • Work distribution keywords: implement, create, add, fix, refactor, update, change, modify, delete, remove, migrate, build, write
  • Tie-breaker: default to Summarize & Index

Scoping:

  • Partition into independent areas
  • One subagent per area or logical group
  • Group coupled paths and related work into one scope
  • Align to monorepo boundaries when present
  • Define output files in advance using agent feature TEMP folder
  • Spawn subagents in parallel if possible to do the work
  • Once work is done spawn another set of subagents to verify that the work was done properly

</core_concepts>

</large_workspace_handling>

Repository
griddynamics/rosetta
Last updated
Created

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