ai.jeda/jeda-ai

DEPRECATED alias for `generate_visual` (removed no earlier than v1.24.x). Use `generate_visual` going forward — identical behaviour.

Runs a specific framework against a user's inputs and produces a full analysis: prose explanation + structured fields + a self-contained SVG visualisation. Powered by the Jeda.ai · Visual AI framework knowledge graph. ALWAYS call `recommend_framework` FIRST to obtain a valid framework_id -- it returns the exact namespaced slug to pass here. Framework ids are namespaced by category (e.g. SWOT = "cms_swot-analysis", Porter's 5 Forces = "cms_porters-five-forces"); a bare slug like "swot-analysis" will 404. REQUIRED post-processing on success: the response's first text block contains a `curl -fsSL` save-directive for the SVG. Save the file locally and surface it as a file chip — do NOT summarise the visual in prose. Input: framework_id (namespaced slug from `recommend_framework`) + user_inputs object (per-framework field set), OR a free-text `raw_prompt` fallback. Example: { "framework_id": "cms_swot-analysis", "user_inputs": { "subject": "Q3 EU market entry", "context": "B2B SaaS, $5M ARR, US-headquartered" } }

Generates a visual (flowchart, mindmap, matrix, timeline, Gantt, ER, sequence, swimlane, block diagram) as a self-contained SVG. Powered by Jeda.ai · Visual AI. REQUIRED post-processing on every success: the response's FIRST text block is a "SAVE THIS NOW" directive with a `curl -fsSL` one-liner (Step 1) and an inline-SVG fallback (Step 2). Always attempt Step 1 first; only fall back to Step 2 if curl exits non-zero. The user expects an "Image · SVG" file chip — not a markdown link or prose summary. The signed URL is safe to fetch (auth is in the query string). Two modes: (1) natural-language `prompt` → Data Agent + Design Agent build the visual; (2) structured `nodes` + `edges` for precise control. Visual types: matrix | mindmap | flowchart | block-diagram | timeline | gantt | er-diagram | sequence | process-flow. Default: auto-detected from prompt. Slash commands work too: `/matrix SWOT`, `/timeline roadmap`, `/process-flow procurement approval with finance and legal lanes`. For style options (themes, fonts, arrow styles, animations, per-edge overrides, matrix/process-flow specifics) call `get_style_options` first. Default theme is `pastel` — only override when the user explicitly names another. Example: { "prompt": "user signup with email verification", "theme": { "preset": "pastel" } }

Returns the full style-options catalog for `generate_visual` — theme presets, fonts, arrow styles, line styles, arrowheads, scene/connector animations, layout directions, per-edge overrides, and matrix/process-flow specifics. Call this once when you need to expose specific style choices to the user (e.g. "what themes are available?") or before composing a `generate_visual` call that needs non-default styling. Output is plain text, ~4 KB.

Recommends business / strategy / risk frameworks for a stated problem. Powered by the Jeda.ai · Visual AI framework knowledge graph (~2,100 frameworks across 19 categories, edge-curated). Use when the user describes a business problem ("customer churn rising", "evaluating market entry", "need to assess vendor risk") rather than naming a specific framework. Returns top-N frameworks ranked by fit, each with a concrete reason citing the specific problem signals matched. Input: just the problem statement is enough. Optional faceted filters (`persona`, `regulation`, `decision_stage`) narrow the candidate set. Set `limit` between 3 and 10 for picker UIs. Pair with `generate_framework_analysis` to actually run a recommended framework against the user's inputs. Example: { "problem_statement": "We need to decide whether to enter the EU SMB market in Q3", "decision_stage": "decide", "limit": 5 }