# Boheling Deltasci Deltasci > DeltaScience: The Grounding Layer (scan → gap → verify) - Skill: `tomevault-io/boheling-deltasci-deltasci` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/boheling-deltasci-deltasci` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/boheling-deltasci-deltasci/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/boheling-deltasci-deltasci --- # DeltaScience: The Grounding Layer (scan → gap → verify) ## Purpose Ground an AI-assisted research idea or draft against the **real record**, in three moves: 1. **Scan** — find the closest existing work (prior art) across OpenAlex, arXiv, PubMed, GitHub. 2. **Gap** — judge whether that space is crowded, contested, or open, and name the distinguishing angle. 3. **Verify** — check every citation against the source of truth: does the identifier resolve, does the metadata match, does the cited paper actually support the claim? ## The one rule that governs everything: no LLM in the trust path There are two kinds of work here, and they are *not* symmetric: - **Discovery (scan, gap) is yours.** You are the LLM. Write the queries, judge which results are genuinely relevant, reason about where the gap is. A weak discovery pass can only make you *miss* a paper — it cannot make a false statement about what exists — so your judgement is welcome here. - **Trust (verify) is the engine's.** A citation is real, and supports its claim, **only when `deltasci verify` says so.** Never assert from memory that a PMID/DOI is valid or that a paper supports a claim. The engine fetches the live record and decides deterministically. This is the entire point of the tool: the verdict must not depend on a model that can hallucinate agreement. If you ever catch yourself about to write "this citation looks correct" without having run `deltasci verify`, stop and run it. ## Prerequisites ```bash pip install deltasci # core engine (keyless) pip install 'deltasci[pdf]' # add PDF support for whole-paper input ``` The engine is deterministic and needs **no API key**. All three commands emit `--json`. ## Inputs | Input | How | |-------|-----| | A research idea / abstract | pass the text | | A paper or draft PDF | pass the path with `--pdf` | | A related-work snippet with citations | pass the text to `verify` | ## Procedure ### Step 1 — Frame the idea Read the idea or the paper's title + abstract. Identify, in the field's *standard* vocabulary: - the **problem** (e.g. "long-horizon sparse-reward credit assignment"), - the **technique** (e.g. "group-based reinforcement learning for LLM agents"), - the **application / domain**. **Critical:** find the paper's own **coined names** — its method, system, or benchmark names (e.g. a made-up acronym like `SkillEvo`, `WebArena-Lite`) — and **set them aside. Never search for them.** No other work uses those terms, so they return nothing and poison a query. This is the single most common reason a scan finds "no prior art" for a hot area. ### Step 2 — SCAN: you write the queries, the engine fetches real records Write 3–5 search queries, most-specific first, collectively covering problem + technique + application, using canonical terms and synonyms. Then issue them with the explicit-query primitive: ```bash deltasci scan \ --query "llm agent reinforcement learning skill" \ --query "long-horizon sparse reward credit assignment" \ --query "group relative policy optimization GRPO" \ --json ``` - For a non-biomedical idea, drop PubMed: `--sources openalex,arxiv,github`. - `--limit 20` for a wider net. Every hit in the JSON is a **real, retrieved record** (title, authors, year, venue, url). Read them and **rerank by genuine relevance** — judge by *meaning*, not shared words. A paper that merely shares vocabulary but solves a different problem is not close. Do **not** invent or embellish any record; only use what the engine returned. If `failed_sources` is non-empty, a corpus was slow/rate-limited — note it as a coverage gap (the run is incomplete, not empty). ### Step 3 — GAP: reason, grounded only in the retrieved works From the real hits, classify the space: - **CROWDED** — strong, direct prior art exists; the researcher should read it before building. - **CONTESTED** — adjacent work exists; a distinguishing angle is needed. - **OPEN** — little direct prior art. Ground every statement in the listed works, naming them by author and year. State what the works already cover and the one **distinguishing angle** the idea leaves open. Never invent a paper to fill the story. **Honesty rule on absence:** you may call CROWDED or CONTESTED freely (you can't un-find a close match). But only call **OPEN** if the scholarly sources (OpenAlex / arXiv / PubMed) actually answered. If one failed, the space is **INCONCLUSIVE — re-run**, never "open." Absence of evidence from a source that didn't respond is not evidence of an open gap. Optional deterministic cross-check (density-based, keyless): ```bash deltasci gap --query "llm agent reinforcement learning skill" --json ``` ### Step 4 — VERIFY: the deterministic engine, never you For any draft, related-work section, or paper that *contains citations*, run the engine. Do not eyeball them. ```bash # A whole paper (parses the bibliography, checks each reference in context): deltasci verify --pdf paper.pdf --json # A snippet of prose with inline identifiers: deltasci verify --text "AlphaFold predicts structure (PMID 34265844). TAMs drive osteosarcoma (PMID 32015508)." --json ``` Report the per-citation verdicts exactly as the engine returns them: - **PASS** — exists and matches what's claimed. - **FABRICATED** — the identifier resolves to nothing; the citation is invented. - **METADATA-MISMATCH** — real identifier, but wrong year/author/title than cited. - **UNSUPPORTED** — real paper, but its abstract does not support the claim it's attached to (likely the wrong paper). `deltasci verify` exits **2** if any audit fails, so it drops straight into CI. Surface FABRICATED / METADATA-MISMATCH / UNSUPPORTED prominently — these are the failures the tool exists to catch. ### Step 5 — Report Give the researcher: - **Prior art** — the closest real works, with links (from scan). - **Gap** — the verdict (crowded / contested / open / inconclusive) + the distinguishing angle, grounded in those works. - **Citations** — the verdict table, with every failed audit called out and a link to the real record. - **Coverage caveats** — any source that didn't respond. - **Handoff** — what only the researcher can decide (is the angle actually novel to *them*; is the unsupported citation a typo or a wrong paper). ## Rules - **Never invent a paper, citation, author, or finding.** scan returns real records; verify checks against the real record. Your contribution to discovery is *queries and judgement*, not facts recalled from memory. - **Never put yourself in the trust path.** "Verified" means `deltasci verify` returned PASS — nothing else. - **Strip the paper's own coined names** from every search query. - **Honest absence.** "Open space" requires the scholarly sources to have actually answered. - **Report verdicts verbatim.** Don't soften a FABRICATED into "couldn't confirm." ## Checklist - [ ] Framed problem / technique / application; coined names set aside. - [ ] 3–5 canonical-vocabulary queries written and run via `deltasci scan --query`. - [ ] Hits reranked by genuine relevance; no fabricated records. - [ ] Gap classified and grounded in named real works; OPEN only if scholarly sources answered. - [ ] Every citation in any draft/paper checked with `deltasci verify` (never from memory). - [ ] Report includes prior art + gap + citation verdicts + coverage caveats + researcher handoff. --- > Source: [boheling/deltasci](https://github.com/boheling/deltasci) — distributed by [TomeVault](https://tomevault.io).