# Ideation > Front stage for /data2story-pro when the reader has no dataset — only a vague idea. Converges the idea into a concrete, data-backed topic through a sparring-partner dialogue (anti-sycophantic, feasibility-pressure-tested), then acquires a REAL dataset through find-data, with a user checkpoint after each. Returns a validated DATA_DIR for the main pipeline. Not a newsroom role — runs upstream of Detective, before any dataset exists. Real data only; never a reason to synthesize data. - Skill: `qinghonglin/ideation` (Agent Skill, multi-file: 3 files) - Install (CLI): `npx skillmds@latest add qinghonglin/ideation` - Raw SKILL.md: https://api.skillmd.com/api/skills/qinghonglin/ideation/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: QinghongLin (https://skillmd.com/u/qinghonglin) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/qinghonglin/ideation --- # Ideation — from a vague idea to a data-backed topic + a real dataset The `/data2story-pro` orchestrator routes here in **IDEA MODE**: the reader handed over a hunch, a question, or a half-formed angle instead of a dataset. Your job is to turn that into a concrete topic that *real, findable data* can support, fetch that data, and hand a validated folder back to the pipeline. You do this WITH the reader, not for them — two real checkpoints, no railroading. You are not a pipeline role (no `*_NN` provenance prefix, no place in the 7 teams). You run once, before Detective, and produce nothing that reaches the HTML except the dataset + a `story_brief`. ## Inputs - `$1` = the reader's raw idea text (may be empty → open by inviting it). - `$2` = `DATA2STORY_ROOT` (resolved by the orchestrator; where `data//` will live). ## Return contract (how the orchestrator continues) - **Success:** emit a final line `DATA_DIR=`. The `story_brief.json` sits at `/meta/story_brief.json`. The orchestrator sets `DATA_DIR`/`DATA_NAME` from this and enters the normal pipeline (Detective → … → Inspector). - **Abort:** emit `IDEATION_ABORTED: ` (reader stopped, or no real dataset supports the idea after the bounded loop). The orchestrator halts honestly and runs NO pipeline. Never fabricate data to manufacture a success. ## The flow — 3 steps, 2 checkpoints **Interaction style — let the reader CHOOSE, don't make them compose.** Drive the convergence and BOTH checkpoints with `AskUserQuestion`: frame the angles / scope / data-forks as options the reader clicks, not paragraphs they must write — picking is far lower-friction and each question doubles as a micro-checkpoint. ALWAYS keep the **Other / free-text** escape open: the menu is your framing, and the reader's own off-menu angle is often the best one, so never let it cage the brainstorm. (This is NOT the cold opening questionnaire `sparring-partner` warns against — it is choice-driven convergence *after* you have framed the space: lead the very first turn with substance + an open invite, then switch to options.) ### Step 1 — Converge the idea (reuse `sparring-partner`) Run the brainstorming dialogue by following **`Skill sparring-partner`** with the mission in [`references/sparring_brief.md`](references/sparring_brief.md): drive the reader from a vague idea to ONE concrete data-story topic. Two non-negotiables on top of sparring-partner's normal process: - **Anti-sycophancy** (its core stance) — do not rubber-stamp the first pretty idea. - **A feasibility pressure-test** — relentlessly ask *does this data actually exist? at what granularity? who publishes it? for which years/places?* A beautiful idea with no obtainable data is a **failure** of this step, not a success. Steer toward a nearby idea the data CAN support. The terminal of the dialogue is the **`story_brief`** (contract: [`references/schema.json`](references/schema.json)) — topic, angle, audience, the questions the data must answer, a structured `data_needs` spec, any **real** candidate sources surfaced, and the exact `find_data_invocation.query`. Reply in the reader's language (sparring-partner's rule). ### CHECKPOINT 1 — confirm the brief Show the reader the assembled `story_brief` (at least `topic`, `angle`, `data_needs`, and `find_data_invocation.query`). Use `AskUserQuestion` (approve · edit · abort) or a plain confirm. Loop back into Step 1 on edits. Do not proceed until the reader approves the brief. On abort → return `IDEATION_ABORTED: reader stopped at brief`. ### Step 2 — Acquire a REAL dataset (reuse `find-data`, web-first) Derive a kebab-case `slug` from `story_brief.topic`; set `OUT_DIR` to the ABSOLUTE path `$2/data/` (resolve `$2` to an absolute path first). Then follow **`Skill find-data`** with the brief's query and ALWAYS pass that explicit `--out OUT_DIR` — never rely on find-data's bare default (its default is `DATASETS_ROOT/`, a DIFFERENT root: `./datasets/`, not `data/`). An explicit `--out` always wins, so the dataset is guaranteed to land at the path ideation chose: ``` Skill find-data "" --out OUT_DIR [--mode ] [other flags] ``` find-data searches (web-first on an open-source machine with no local corpora), fetches, and runs its 4 completeness gates, writing `OUT_DIR/validate.json`. Read that file back for the verdict. The dataset files land directly under `OUT_DIR`, and the `DATA_DIR` returned to the orchestrator (the success line below) is exactly that absolute `OUT_DIR` — not find-data's default location. **Bounded acquisition loop (≤ 2 attempts).** If find-data returns BLOCKED / no adequate dataset: 1. Surface honestly what was and wasn't found (the failing gates). 2. Offer the reader: **(a)** re-enter Step 1 to pivot/narrow the topic (often the data exists only at a coarser granularity — adjust the brief), **(b)** try an alternate real source/query, or **(c)** abort. 3. Never invent a dataset, a source URL, or a license to "succeed." After 2 failed attempts with no path forward → return `IDEATION_ABORTED: no real dataset supports this idea (closest gap: ); suggested pivot: `. ### CHECKPOINT 2 — confirm the dataset Show the reader the fetched files + the gate verdict, and check them against `story_brief.acceptance` (does it actually have the entities / metric / coverage you agreed on?). `AskUserQuestion` (use it · send back to Step 2 · abort). Do not proceed until approved. ### Step 3 — Finalize + hand off Only AFTER find-data's audit has run (so it never lands inside the data-file glob), write the approved brief to `OUT_DIR/meta/story_brief.json`: ```bash mkdir -p "OUT_DIR/meta" && # write story_brief.json there (valid JSON matching references/schema.json) ``` It carries the reader's intent into provenance; the Detective MAY read it for human-intent context (loose coupling — not required). Then emit the success line: ``` DATA_DIR=OUT_DIR ``` ## Guardrails - **Real data only.** No synthesis, no simulated rows, no fabricated source URLs or licenses — that would break the whole verifiability premise. "Can't find data" is an honest `IDEATION_ABORTED`, not a reason to invent it. - **Checkpoints are real stops.** The reader drives; you converge with them, not at them. - **Portability.** No hardcoded machine paths — derive everything from `$2` and the resolved skill dir. Works on a fresh open-source clone with no local data corpora. - **Stay in your lane.** You write only inside `OUT_DIR` (the dataset folder). You do not build HTML, run the pipeline, or touch any role artifact — that's the orchestrator's job after you return. ## Reference files - [`references/schema.json`](references/schema.json) — the `story_brief` contract (annotated example). - [`references/sparring_brief.md`](references/sparring_brief.md) — the specialized mission handed to `sparring-partner`, with the feasibility pressure-test and a worked vague-idea → brief example.