Individual skill
exa-core-workflow-b
Run asynchronous Exa Agent research with a bounded schema, effort, terminal-state policy, citations, and cleanup decision. Use when operating or reviewing this Exa boundary. Trigger with "Exa core workflow b", "review Exa core workflow b", or "fix Exa core workflow b".
plugins/saas-packs/exa-pack/skills/exa-core-workflow-b/SKILL.md
Source commit 0500b275e963c027f6b410e8c49c0446945c574e
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- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
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- Observed behavior
- Not checked yet
- Last checked
- Nov 12, 2026
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Repository context
- Repository stars (not skill ratings)
- 2,916
- Repository last updated
- Nov 12, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- saas Declared skill tag
- exa Declared skill tag
- research Derived category
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SKILL.mdcore · 4,808 bytesreferences/official-docs.mddoc · 1,835 bytes
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# Exa Agent Run Lifecycle
## Overview
Run asynchronous Exa Agent research with a bounded schema, effort, terminal-state policy, citations, and cleanup decision. Treat credentials, queries, retrieved content, generated output, spend, and destructive state as separately governed boundaries.
## Prerequisites
- The target repository, environment, Exa team, product surface, and accountable owner.
- The workload's data classification, latency and freshness promise, cost ceiling, and retention policy.
- Current first-party documentation plus credentials only for a narrowly approved live check.
## Current Contract
Agent runs are asynchronous unless streamed. A created run returns an ID that must be polled, streamed, stopped, cancelled, or deleted through the Agent lifecycle. Fixed effort provides a predictable price; auto and beta max are usage-metered. Structured output and grounding require separate validation.