dispatching parallel agents
Explore dispatching parallel agents as a productivity & planning workflow from obra/superpowers. Compare its source, maintenance and review signals before choosing it for your agent.
A Tavily hosted-research workflow for multi-source synthesis with retained citations.
Editorial review checked 2026-10-29 against this instruction snapshot. Supporting scripts and runtime behavior remain outside this editorial review.
The source describes a longer research operation with model selection, streaming, structured output and saved reports. It positions this after simpler retrieval options when the task needs synthesis rather than a quick fact. The resulting report is an input to review, not a substitute for reviewing evidence.
A bounded comparison or background investigation where multiple sources and a traceable written synthesis are useful.
This operation requires authentication and hosted processing may incur costs. A report with citations can still misstate what sources say or omit relevant counterevidence. Sensitive questions or documents need an explicit decision before sending them to an external service.
Unknown; inspect source requirements and supporting scripts.
Inspect the pinned source snapshot and its supporting files first. The command selects this skill through the open-source skills CLI. Node.js and agent-specific setup may be required. Installation can download code. Catalog ingestion never executes skill instructions or install scripts.
npx skills add https://github.com/tavily-ai/skills/tree/778122e5f9c680f541eeceda5a5b36405eb7980c/skills/tavily-research --skill tavily-researchReview pinned skill folder ↗ · CLI documentation ↗
After source review, use npx skills check and npx skills update to inspect and apply upstream updates. Re-check changed instructions before running them.
Static review only. This is not a security audit or a guarantee of safety.
SKILL.md text only; scripts, dependencies and runtime behavior not audited.
Allowed tools declaration: Bash(tvly *). Runtime permissions and network behavior: Unknown.
85/100 · Metadata coverage 100% · Model 1.0
Scores summarize observable discovery signals. Popularity and repository activity apply to the whole repository. Unknown runtime safety earns no certification.
Define the question, required evidence and output shape, then choose a suitable research scope. Preserve the returned report and citations so that conclusions can be checked independently.
Open the most consequential cited sources, compare their claims and dates, and flag unresolved disagreements. Verify structured output against its schema and distinguish source-supported conclusions from synthesis or inference introduced by the research service.
Related by category; compare scope and dependencies before choosing an alternative.
Explore dispatching parallel agents as a productivity & planning workflow from obra/superpowers. Compare its source, maintenance and review signals before choosing it for your agent.
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A Tavily SDK integration guide that separates search, extraction, discovery, crawling and research.
A bounded Tavily crawling workflow for collecting several pages from a defined website section.
A Tavily workflow for filtering large retrieval payloads before they enter an agent’s working context.