# Grounded > Produce source-grounded scientific narrative reviews, or audit the claims and references of a supplied draft, using live literature discovery, verified bibliographic records, independent claim checking, and evidence receipts. Supports chat and journal PDF output. - Skill: `jostelzer/grounded` (Agent Skill, multi-file: 95 files) - Install (CLI): `npx skillmds@latest add jostelzer/grounded` - Raw SKILL.md: https://api.skillmd.com/api/skills/jostelzer/grounded/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Product & Planning - Author: jostelzer (https://skillmd.com/u/jostelzer) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/jostelzer/grounded --- # Grounded Make an article worth reading: answer the research question through a clear, engaging explanation and figures that teach. For popular science, a sustained story must draw the reader in and develop their understanding. Editorial quality and scientific integrity are both required; an accurate inventory of findings is unfinished work. Keep verification in the working process and compact evidence apparatus, while the article follows its subject. Find citations through live search, read their sources and independently check assertions. Receipts establish attribution, not truth or a good article. Choose the structure that supports the reader's task. Popular science develops curiosity through a story; ELI5 builds a concrete explanation with no assumed expertise and no compulsory story; scientific writing states the assessment early and develops an evidence-led synthesis. Here, **narrative review** names the review methodology, not a requirement for storytelling. Use the selected style's planning and editorial criteria in `references/writing-guide.md`. ## Route the request - **Review:** preserve the user's choices. Infer missing dimensions from the request; otherwise use medium, popsci, journal PDF. Start work without a size/style/format question. Ask only if ambiguity would materially change the research question, audience, or deliverable. - **Draft check:** audit the supplied text; do not replace it with a new review. Follow `references/draft-check.md`. Unsupported claims and unresolved sources are findings, not reasons to suppress the report. - **Slides:** only when explicitly requested. Read `references/deck-guide.md` and the slides section of `references/output-formats.md`. Slides remain experimental and lack assertion receipts; disclose that limitation. Never describe a deck as having the written-review audit. Keep one case directory with the ledger, search manifest, reading notes and authenticated texts, synthesis, evidence assessment, draft, evidence store, and audit. Preserve failed attempts as audit history. For multiple journal reviews, also read `references/production-workflow.md`. Budgets come from `scripts/review_config.py`; the generated table is `references/budgets.md`. Size controls scope and length, not a quota of references. Never include an irrelevant paper to hit a count. Use the existing documented-saturation override when a thin field cannot meet search or full-text targets. ## 1. Establish access and scope Check literature API access before drafting: ```bash python3 -c "import urllib.request;print(urllib.request.urlopen('https://api.crossref.org/works/10.1136/bmj.n71',timeout=15).status)" ``` On failure, diagnose connectivity, credentials, rate limits, and available supported access paths. Do not assume capabilities from the host's product name. If required verification remains unavailable, report the actual blocker; do not present unverified evidence as verified. Record the question, population/model, comparison, outcomes, inclusion/exclusion boundaries, and review type before searching. Default to a **narrative review**; use systematic-review terminology only when protocol, search, and screening methods justify it. ## 2. Discover and read Read `references/search-playbook.md`. Search reviews, primary evidence, recent work, and contrary/null findings with `scripts/find_papers.py`; use stable angle IDs and funnel lanes. Chase central papers for medium and large reviews. Run `scripts/audit_search.py search-manifest.json --size `. A contrary/null search must complete at every size. Finding disagreement is not required: report that none was found within the searched scope when that is what happened. Failed calls are not saturation. Read every cited abstract and obtain full text for load-bearing claims. Save full texts under ledger keys and record design/sample, result, limitation, and synthesis use in notes. Run `scripts/audit_fulltexts.py` as specified in `references/quality-gates.md`. Missing text limits what may be claimed; never guess inaccessible methods or results. For popsci, also gather material for the story while reading: the observation that needs explaining, what an investigation actually did, and how a finding changed the question. Use `references/style-popsci.md`; record sourced details in the existing notes and synthesis rather than trying to decorate a finished evidence summary afterward. Run `scripts/verify_citations.py --ledger sources.json`. Peer-review eligibility, bibliographic identity, integrity screening, and text access are separate checks. Crossref's absence of an integrity signal means **no signal found in the queried data as of the check date**, not proof that no correction or concern exists; inspect publisher notices for load-bearing sources and recorded corrections. ## 3. Assess and synthesize Read `references/evidence-weighing.md`, `references/synthesis-guide.md`, and `references/interpretation-review.md`. Preserve the question each source actually answers; attribution, interpretation and evidence strength are separate judgments. Write atomic, calibrated claims in `synthesis.md`, with source keys, verbatim quotes, boundaries, contrary evidence if found, dependencies, and exact quantities. Create `evidence-assessment.json` following `references/evidence-assessment.md`. For every synthesis claim, record outcome certainty and reasons across risk of bias, inconsistency, indirectness, imprecision, and publication bias. Group publications from the same study and record overlap between reviews. Unknown overlap cannot count as independent corroboration. These are structured judgments, not automatically certified GRADE ratings. ```bash python3 scripts/verify_claims.py seed --ledger sources.json --evidence evidence/ --fulltext-dir fulltexts --fulltext-manifest fulltext-manifest.json python3 scripts/verify_claims.py synthesis-check --synthesis synthesis.md --ledger sources.json --evidence evidence/ --assessment evidence-assessment.json --report synthesis-check.json ``` Fix failed evidence checks before drafting. Derived arithmetic must be explicit and reproducible; never change units or convert an association into causation merely to simplify prose. ## 4. Write and produce the selected format Read `references/writing-guide.md` and only the selected `style-scientific.md`, `style-popsci.md`, `style-bullets.md`, or `style-eli5.md`. Plan the developing explanation and the figures' contribution in the synthesis's existing Throughline field. For popsci, compose a feature with an inviting opening, a story sustained through the body and an earned payoff. Complete the editorial read before media production; each figure must earn its place by making a specific relationship easier to understand. If the scientific meaning changes, update the synthesis and assessment first. Cite claims with ledger keys, then use `scripts/format_references.py` and `scripts/validate_review.py` as specified in `references/quality-gates.md`. Include a compact scope/methods disclosure: narrative/systematic status, search date, databases, boundaries, and material access limitations. Keep it separate from the main explanation. Findings must distinguish text access, source support, and evidence certainty. For PDF or slides, read the selected section in `references/output-formats.md` and its linked media contracts. Select complementary explanatory illustrations and quantitative plots by evidence and purpose, without a fixed ratio or padding; discover the actual image tools, including deferred tools, before claiming image generation is unavailable. Use the available image generator for illustrations and deterministic plots for exact quantities. Preserve the canonical renderer, figure provenance, and visual QA. Inline chat needs no media workflow. Figures and captions must be finished before the written-review assertion audit. ## 5. Independently audit all assertions Follow `references/claim-verification.md`. Use a fresh independent judge. It must qualify on the unlabelled, multi-domain benchmark; gold answers stay outside its context. Require complete coverage, at least 80% verdict agreement, and zero false acceptance on the supplied qualification set. The older creatine benchmark is additional calibration, not sufficient qualification. ```bash python3 scripts/verify_claims.py extract --review review.md --ledger sources.json --synthesis synthesis.md --assessment evidence-assessment.json --audit claims_audit.json python3 scripts/verify_claims.py fetch --audit claims_audit.json --evidence evidence/ --ledger sources.json --fulltext-dir fulltexts --fulltext-manifest fulltext-manifest.json python3 scripts/verify_claims.py packets --audit claims_audit.json --evidence evidence/ --blind ``` The inventory includes uncited text, headings, summaries, table cells and captions. The independent judge classifies each uncited item as factual, interpretation with factual basis IDs, nonfactual with a reason, or document-local artifact evidence with inspected file hashes and a substantive reason. Artifact evidence is restricted to local provenance or depicted geometry, never scientific factual claims. A factual item without evidence cannot ship. Citation-free abstracts and summaries must map their assertions to checked factual claims, not disappear from the audit. Judge source support per assertion element and record inspected context and interpretation under `references/interpretation-review.md`. A partial source may ship only if other evidence covers the remainder; every element must be supported. Never drop a citation while leaving its unsupported assertion behind. Repair the prose or evidence, re-extract, and re-adjudicate changed assertions. Afterward, re-read the whole article for continuity and reporting voice and inspect the actual figure pixels. Record the reader's takeaway, the explanation's progression and its checked basis with `review-context`. Reopen synthesis when selection, framing or compression changes the inference. ```bash python3 scripts/verify_claims.py check --audit claims_audit.json --evidence evidence/ --summary claims_summary.json --strict python3 scripts/verify_claims.py receipts --audit claims_audit.json --review review.md ``` Receipts, export, and PDF QA bind the exact assertion inventory and evidence versions to the checked audit. Legacy audits must be re-extracted and checked. Modifying claims, classifications, source assignments, or saved evidence invalidates the release. An audit hash establishes consistency, not independence or truth. ## 6. Deliver Write the review in chat; deliver any requested PDF and the receipts alongside it. State the source-access split and the outcome certainty honestly. For PDF, run the mandatory release QA and inspect every rendered page before delivery. Follow `references/output-formats.md` for the export command and lineage files. Preserve the audit inputs for inspection. Do not claim live checks, independent judgment, source access, or successful QA that were not performed. When changing scientific or writing rules, use `references/generalization-evaluation.md`: freeze rules before independent evaluation, separate regressions from held-out cases, and assess editorial quality separately from source interpretation. Report false acceptance and false rejection for scientific judgments. A passing schema or quotation match validates neither judgment nor readability.