Loading...
Loading...
Found 95 Skills
Choose the right Parallel API and configuration for cost, latency, and answer quality. Use when adding live web data to an app: current events and prices, a cited answer in a chat, grounding an agent in sources it can read in full, reading a URL or PDF, deep research reports, researching or enriching every row of a list or CRM. Use when picking among Search and Extract, Responses, and Task, or when choosing a search mode, reasoning effort, or Task processor. Also use when an integration is too slow, costs more than expected, or misses answers that are on the web.
Get completed research task result by run ID
Set up the Parallel plugin (install CLI)
Discover entities (companies, people, products, etc.) matching a natural-language description. Use when the user asks to 'find all X' or 'list every Y that…' — e.g., 'Find AI startups that raised Series A in 2026', 'List roofing companies in Charlotte NC', 'Show me YC W24 dev tools companies'. Different from web-search (which returns webpages) and deep-research (which returns a narrative report). Use this when the user wants a structured list of entities.
Recall past Parallel Task, Monitor, and FindAll runs when they may help; evict runs or clear memory when asked.
Use when verifying, using, or troubleshooting the anonymous Parallel Search MCP server bundled with this plugin — when the user installs the plugin, says "set up Parallel Search", "Parallel search isn't working", hits 429 rate limits from Parallel, or asks how to get higher limits. Also covers how to use the web_search and web_fetch tools the bundled server provides. For an authenticated gateway deployment use parallel-mcp-setup; for the CLI-backed skills use parallel-cli-setup.
Use when installing, configuring, or troubleshooting an authenticated Parallel Search MCP connection in Bifrost, including gateway-level search settings and downstream tool access.
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
Spawn Codex subagents via background shell to offload context-heavy work. Use for: deep research (3+ searches), codebase exploration (8+ files), multi-step workflows, exploratory tasks, long-running operations, documentation generation, or any other task where the intermediate steps will use large numbers of tokens.
Comprehensive codebase review and parallel agent-based remediation skill. Use PROACTIVELY when agent needs to perform full codebase audit, generate master findings report with quantified metrics, and execute remediation using parallel goodvibes background agents (max 6 concurrent, one task per agent with fresh context). Triggers on: codebase review, code audit, full project analysis, quality assessment, technical debt analysis, parallel remediation, bulk fixes.
Use this skill when orchestrating multi-agent work at scale - research swarms, parallel feature builds, wave-based dispatch, build-review-fix pipelines, or any task requiring 3+ agents. Activates on mentions of swarm, parallel agents, multi-agent, orchestrate, fan-out, wave dispatch, research army, unleash, dispatch agents, or parallel work.