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global/research-to-hooks

Research → Hooks — deep research a topic, then generate hooks from the findings.

Category: global
Source: workflows/research/research_to_hooks.py

FieldTypeDefaultDescription
queryobject
regenerateobjectWhen set, this run is a regeneration. Workflows may read direction / keep / extra_instructions to modulate prompts; the engine persists parent_run_id and parent_variant_index as run lineage columns.
variantsinteger1Number of independent variant executions (1–10). When > 1, the engine runs the workflow N times with different sampling, producing N outputs.

No schema defined.

plan_research → search_web → read_webpages → research_youtube → fetch_rss_feeds → search_reddit → merge_research → synthesize_research → format_report → bridge_research_to_hooks → generate_hook_ideas
TaskDescription
plan_researchValidate input and decide which sources to activate.
search_webSearch the web via Exa (semantic search) or Jina Search (free fallback).
read_webpagesRead top web results as clean markdown via Jina Reader (free, no API key).
research_youtubeSearch YouTube for relevant videos and extract metadata + transcript excerpts.
fetch_rss_feedsParse RSS/Atom feeds for latest content.
search_redditSearch Reddit via shared Reddit client (old.reddit.com, UA rotation, retry).
merge_researchJoin function — merge parallel branch outputs into a unified context.
synthesize_researchAnalyze all collected sources with Gemini and produce a structured synthesis.
format_reportStructure the final output, stripping internal keys.
bridge_research_to_hooksTransform deep-research output into hook-generation input.
generate_hook_ideasGenerate hook ideas — delegates to SDK stage (70/20/10 strategy, PromptExtension).

Save the YAML below as my-run.yaml, edit the values, and run with the CLI or POST it to the API. Required fields are uncommented; optional knobs are documented above the input: block — copy any line under input: and uncomment to set.

workflow: global/research-to-hooks
# Optional fields — copy any line(s) under `input:` and uncomment to set:
# query: null
#
input: {}

Run it locally:

Terminal window
fab-workflow --from-file my-run.yaml

Or submit over the wire — the same file is the request body:

Terminal window
curl -X POST 'https://gofabric.dev/v1/workflows/runs?name=global/research-to-hooks' \
-H 'Authorization: Bearer fab_xxx' \
-H 'content-type: application/yaml' \
--data-binary @my-run.yaml

Every workflow also accepts the universal WorkflowInput fields — variants (1–10 fan-out) and regenerate (creative-direction hints with run lineage). See Run-specs (YAML / TOML / JSON) for the full top-level shape (metadata, priority, bundle, parent, etc.).

  • Last user task generate_hook_ideas has no Pydantic return type — workflow output schema is null. Declare a WorkflowOutput subclass and pass it to Flow(output=…) for a strict contract.
  • Task merge_research has no Pydantic types — contract is opaque to consumers.
  • Task generate_hook_ideas has no Pydantic types — contract is opaque to consumers.