external-research-fleet
SolidOrchestrator-workers variant of external-research for multi-modal sweep across distinct angles or source-groups of one research question. Promotes external-research's inline delegation to a first-class orchestrator with a worker contract and provenance. Sonnet orchestrator dispatches N Sonnet workers (one angle each) in parallel; each produces a structured per-angle synthesis grounded in REFERENCES.md; orchestrator merges into a single EXTERNAL_RESEARCH.md with cross-angle reconciliation (reinforcing vs contradicting vs different-framing). Use when the research question has N >= 3 distinct angles or source-groups AND the question would benefit from parallel deep reads. Do not use when 1-3 sources suffice (use external-research inline), when one source already dominates (no parallelism gain), or when sources have not yet been captured (run capture-references first).
Install
Quality Score: 81/100
Skill Content
Details
- Author
- Mozurok
- Repository
- Mozurok/fhorja.dev
- Created
- 1 months ago
- Last Updated
- 5 days ago
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
external-research
Synthesize multiple external sources into a task-scoped EXTERNAL_RESEARCH.md grounded in REFERENCES.md entries. Each source is captured first via capture-references (project-level memory; deduplicated by URL); this command produces the synthesis with comparative analysis and a model recommendation visually separated from the source-grounded findings. Never invents claims; grounds every conclusion in a captured source. Use when the task depends on multiple external sources (vendor comparisons, regulatory evaluations, framework choices), when synthesis (not just capture) is needed, or when planning is blocked until external context is digested. Do not use when a single source suffices (use capture-references), when the research is project-level (use capture-references), when the question is internal (use code-locate or impact-analysis), or when no active task folder exists yet (run task-init first). For 3 or more distinct angles, use external-research-fleet.
feature-library-scout-fleet
Orchestrator-workers variant of feature-library-scout for deep per-feature-problem library research. The orchestrator derives the feature-problem list and dispatches one Sonnet worker per problem; each worker ranks candidate libraries by adoption signal (registry downloads, dependents, last release, stars and trend, maintenance, framework/platform fit) relative to the project's ecosystem, grounded in captured REFERENCES.md sources, and returns a typed payload via StructuredOutput; the orchestrator is the sole writer that merges into one FEATURE_LIBRARIES.md and runs the orphan-scan gate (ADR-0038, ADR-0045). Stack-agnostic (npm, PyPI, crates.io, Go, Maven). Use when the product has 3 or more distinct feature problems that each warrant a deep multi-angle read. Do not use for 1-3 problems (use feature-library-scout inline), to pick stack layers (use stack-recommend), to verify framework pattern currency (use stack-currency-check), or with no active task folder (run task-init first).
research-fleet
Parallel research using Fleet wave mechanics. Spawns multiple scout agents, each investigating a different angle of the same question. Findings are compressed between waves. Produces a unified research brief from multiple independent perspectives.