Playbook
Useai_inference for plain text or structured-output model calls with no tool use.
Model IDs are case-sensitive. Use the exact id string from the live
AI Gateway model catalog; the current
Deepline default is openai/gpt-5.6-luna. The tools describe CLI also shows
the selected model metadata and provider option schema:
deepline tools describe ai_inference --model openai/gpt-5.6-luna --json.
For inference and deeplineagent, read toolResponse.raw.result.text for
text, toolResponse.raw.result.object for optional structured data, and
toolResponse.raw.extracted_json for the compatibility JSON field. For
ai_evaluate, use toolResponse.raw.result.answers and
toolResponse.raw.extracted_json.
Use deeplineagent when the task benefits from streaming output and tool use across the current whitelist: serper_google_search, exa_search, firecrawl_scrape, firecrawl_map, firecrawl_crawl, and bash.
For research tasks, prefer an adaptive loop: cheap Serper search first, synthesize, then only run targeted Exa follow-up searches if key gaps remain.
When using exa_search, prefer type: "auto" with contents.highlights and no contents.summary; highlights are token-efficient snippets, while summaries add an extra AI pass.
Use Firecrawl only after you know the target site or section. Prefer firecrawl_scrape for one known URL, firecrawl_map for URL inventory before crawling, and keep firecrawl_crawl tightly scoped with explicit low limit, includePaths/excludePaths, or maxDiscoveryDepth. Firecrawl work scales with discovered pages, crawled pages, and requested modifiers, so do not run broad speculative crawls.
When bash is enabled, /refs/prompts.json is available as a lazily loaded reference file for GTM prompt-template lookup.
Prefer Deepline-native tools over freeform bash when structured provider actions already exist.