Menu

Individual skill

ts-idea2story

0upvotes

Turn a raw research idea into a compelling, well-grounded research STORY (an 8-field structured proposal) ready to feed the ts-paper pipeline. Claude does almost everything natively — idea packaging, recall reasoning over a knowledge graph, agentic external literature search (WebSearch/WebFetch), story generation, and a critique→refine→fusion loop; tiny scripts do only embeddings/recall math and the schema gate. Emits story.json + story_proposal.md + retrieved_papers.json (a citation seed the cite stage reuses, so paper-writing searches less). Use when the user has an idea (not yet a full proposal) and wants a paper-ready story.

skills/ts-idea2story/SKILL.md

Read pinned source

Source commit c17149def034bc777462de612926c8e3b6d01b8c

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
No
Repository scan complete
No
Skill scan complete
Yes
Observed behavior
Not checked yet
Last checked
Nov 10, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
1,200
Repository last updated
Aug 22, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# ts-idea2story — idea → grounded research story (the upstream of ts-paper)

Distilled from the product's idea→story link. **The idea is the PROTAGONIST; a recalled/searched
pattern is the TOOL it wields.** Claude is the packager, the recaller, the searcher, the storyteller,
and the critic — all in one context (so coherence and anti-stacking come for free). Two scripts are
irreducible: `kg_recall.py` (vector/graph retrieval) and `story_lint.py` (the gate); embeddings
(optional) reuse `../ts-kg-build/scripts/embed.py`'s `TS_EMBED_*` config.

## Inputs / Outputs
**In:** a raw idea (text); optional `kg/` dir (from `ts-kg-build`, or the bundled `kg_ts`); optional
`TS_EMBED_*` endpoint; a `retrieval_focus` dial in {trust_kg, balanced, go_search_web}.
**Out (in the workdir):**
- `story.json` — the 8 fields: `title, abstract, problem_framing, gap_pattern, solution,
  method_skeleton, innovation_claims[], experiments_plan`.
Back to top