Install
$ agentstack add skill-qinghonglin-data2story-skill-data2story ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Data Journalist Agent (Data2Story)
Turn $ARGUMENTS into a blog. Orchestrates the roles below in sequence.
Setup
Resolve paths before doing anything:
- Never hard-code machine-local paths and never ask the user to export path variables.
- Resolve
SKILL_DIR= the directory containing thisSKILL.md(.../skills/data2story) - Resolve
ARCHIVE_DIR= the ancestor directory that containsskills/(two levels up fromSKILL_DIR, i.e.SKILL_DIR/../..) - Resolve
DATA2STORY_ROOT= parent ofARCHIVE_DIR - Commands below use symbolic placeholders such as
ARCHIVE_DIR; replace them with resolved, quoted paths before running Bash. DATA_NAME= the dataset folder name (e.g.pick_a_card)DATA_DIR= if$ARGUMENTSis an existing path, use that path; otherwise useDATA2STORY_ROOT/data/{DATA_NAME}TIMESTAMP= current time formatted asMMDD_HHMM(e.g.0401_1618):date +%m%d_%H%M(run in bash)PROJECT_DIR=DATA2STORY_ROOT/project/{DATA_NAME}/blog_{MODEL}_{TIMESTAMP}- Create
PROJECT_DIR/,PROJECT_DIR/assets/,PROJECT_DIR/code/
Archival
Immediately after creating PROJECT_DIR, snapshot the current skills:
mkdir -p PROJECT_DIR/archival
cp -r ARCHIVE_DIR/skills PROJECT_DIR/archival/skills
This preserves the exact skill versions used for this run.
Tools available
All media tools route through OpenRouter. Set OPENROUTER_API_KEY before any generation call.
Media generation is the Designer's job, so the media tools (text2image, text2video, image2video, text2music, embeddings) live under SKILL_DIR/designer/scripts/openrouter-*/. The full list — default models and exact python3 ... invocations — is in [designer/references/tools.json](designer/references/tools.json); full per-tool docs are each tool's own SKILL.md under SKILL_DIR/designer/scripts/openrouter-*/.
Pipeline Overview
The pipeline is a single linear sequence that produces a traceable HTML blog from raw data:
DATA → Detective → Analyst → Editor → Designer → Programmer → Auditor → Inspector → final index.html + viewer.html
Run each stage in order. Each stage reads the previous artifact(s) before starting. Do not proceed to the next stage until the current artifact is complete.
Stage 1 — Detective
Input: DATA_DIR Output: PROJECT_DIR/detective.json What: Researches external context — background knowledge, domain history, related findings, why this data matters. Each finding gets a det_xx ID.
Stage 2 — Analyst
Input: DATA_DIR, PROJECT_DIR/detective.json Output: PROJECT_DIR/code/*.py, PROJECT_DIR/analyst.json What: Exhaustive quantitative analysis of the data, informed by detective's context. All code saved to code/ as runnable scripts. Each finding gets an ana_xx ID with calculation (file + lines + output) and data_table (chart-ready data).
Stage 3 — Editor
Input: PROJECT_DIR/detective.json, PROJECT_DIR/analyst.json Output: PROJECT_DIR/editor.md, PROJECT_DIR/editor.json What: Editorial decisions — which findings matter, what the narrative arc is, what the blog argues. Each section gets an edt_xx ID with explicit references to ana_xx findings and det_xx context. No visual design.
Stage 4 — Designer
Input: PROJECT_DIR/editor.md, PROJECT_DIR/editor.json, PROJECT_DIR/analyst.json Output: PROJECT_DIR/designer.json, PROJECT_DIR/assets/* What: Data-driven creative visual decisions — how to present each point using charts, images, video, audio, maps, interactives, stat callouts, instances, or text-only treatment when appropriate. The media mix should emerge from the dataset's properties, not from a fixed checklist. The page should be multimedia-rich by default: borrow the visual language from the shared [frontend-design](../frontend-design/) skill and use all five channels (chart, image, video, audio, interactive/map) unless a channel's documented fallback would be fabricated or purely decorative. Each visual gets a des_xx ID with data_source pointing to ana_xx data_tables when data-driven. Generates selected assets. No HTML.
Stage 5 — Programmer
Input: PROJECT_DIR/editor.md, PROJECT_DIR/editor.json, PROJECT_DIR/analyst.json, PROJECT_DIR/designer.json Output: PROJECT_DIR/index.html What: Implements the final blog in HTML. Applies the theme/accent recorded in designer.json page_rhythm and borrows component + token recipes from the [frontend-design](../frontend-design/) skill. Resolves chart data from analyst.json data_tables (NO raw data access). Tags every element with data-edt, data-ana, data-det, data-des attributes for traceability.
Stage 6 — Auditor
Input: PROJECT_DIR/index.html Output: PROJECT_DIR/index.html (modified), PROJECT_DIR/auditor.json What: Detects and fixes layout issues (overlap, spacing, alignment) without changing content or design intent. Runs automatically after Programmer to ensure visual elements are properly wrapped and spaced.
Call: Skill auditor PROJECT_DIR
Stage 7 — Inspector
Input: PROJECT_DIR/index.html, all JSON files Output: PROJECT_DIR/inspector.json, PROJECT_DIR/viewer.html What: Runs sentence-level traceability verification and generates an interactive viewer. Two steps:
python3 SKILL_DIR/inspector/scripts/verify.py PROJECT_DIR --log-errors
python3 SKILL_DIR/inspector/scripts/generate_viewer.py PROJECT_DIR
Step 1 produces inspector.json (sentence→evidence mapping). Step 2 produces viewer.html (self-contained, works on file:// — no server needed). See inspector/SKILL.md for details.
Traceability: ID flow through the pipeline
det_01 ──┐
det_02 ──┤
├──▶ ana_01 (based_on: [det_02]) ──┐
│ ana_02 (based_on: []) ├──▶ edt_01 (findings: [ana_01, ana_02], context: [det_01]) ──▶ des_01 (section: edt_01, data_source: ana_01)
│ ana_03 (based_on: [det_01]) │ edt_02 (findings: [ana_03], context: [det_02]) ──▶ des_02 (section: edt_02, data_source: ana_03)
└────────────────────────────────────┘
Every value in the final HTML can be traced: HTML data-des="des_01" → designer.json des_01.data_source="ana_01" → analyst.json ana_01.calculation.code → verifiable.
Handoff rules
- Each artifact must be complete before the next stage starts.
- If an artifact is missing required sections, fix it before proceeding.
- Media-richness gate (after Designer, before Programmer):
designer.jsonshould exercise all five channels (chart, image, video, audio, interactiveormap). For any channel markedused:false, confirm its documented fallback was genuinely tried and a data-grounded reason recorded inmeta.media_decisions. If a channel was skipped for convenience rather than because the data can't support it, send it back to the Designer before the Programmer runs. - All generated assets go into
PROJECT_DIR/assets/only. - Final deliverables:
PROJECT_DIR/index.html,PROJECT_DIR/detective.json,PROJECT_DIR/analyst.json,PROJECT_DIR/code/*.py,PROJECT_DIR/editor.md,PROJECT_DIR/editor.json,PROJECT_DIR/designer.json,PROJECT_DIR/inspector.json,PROJECT_DIR/viewer.html.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: QinghongLin
- Source: QinghongLin/data2story-skill
- License: MIT
- Homepage: https://data2story.github.io/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.