Menu

Individual skill

ts-paper-cite

0upvotes

Stage 2 of the ts-paper suite. Build a complete, REAL refs.bib for a Traitement du Signal paper — using the user's provided references first and Claude's native WebSearch/WebFetch only for genuine gaps. Every entry must have full metadata (authors, year, venue, vol(issue):pages, DOI); never a title-only stub; reference count is driven by real evidence, not a quota. Use when assembling or fixing the bibliography of a TS paper, or whenever citations must be real and complete.

skills/ts-paper-cite/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-paper-cite — real, complete citations (no fabrication)

Citations support real claims with real evidence. **Every entry in `refs.bib` is a paper that
actually exists and that you verified.** This stage replaces the original 100+-call retrieve→triage→
slot→bind→postdraft engine (which fabricated title-only stubs to hit hardcoded quotas) with a few
Claude reasoning passes + native web search.

## Procedure — broad systematic retrieval, then triage (adopt the original engine's *coverage*, keep integrity)
A TS journal paper is expected to be **well-read**: it situates itself in a full literature, not a minimal one. Do NOT stop at "just enough" — search **broadly and systematically**, then keep only the real, well-matched papers. This is the original product's strength (systematic query planning → retrieve many → triage), minus its fabrication.

0. **Reuse the idea2story seed first (if present).** If `retrieved_papers.json` exists in the workdir (written by **ts-idea2story**, which already searched the literature), ingest it as a **verified seed**: for each paper run `scripts/doi2bib.py <doi>` to upgrade it to complete BibTeX (the DOI must resolve, or drop it — Crossref is authoritative over the seed's own metadata), and use its `abstract`+`supports_claim` to place it into `claims_map.json`. This is NOT a free pass — it removes the cold-start sweep, but you still verify each, place by abstract, and gap-fill below. Then the angles you must still search are the ones the seed does NOT cover.
1. **Plan the search angles (query packs).** From the proposal + blueprint (and what the seed already covers), enumerate the angles a thorough reviewer expects covered, and write them to **`retrieval_plan.md`**:
   - the **core task** and its canonical benchmark/problem papers;
   - **each method component / technique** the paper builds on (every named module, predictor, feature, loss);
Back to top