cite-holmes (Cite Holmes): deep research with citation verification

One line: a question goes in — a verified report comes out.

Three differences from a plain "search and summarize":

1. Calibrate before working — ask sharp questions first; the most expensive waste is researching the wrong question.
2. Conclusions carry evidence grades — 🟢 two independent sources agree / 🟡 single authority / 🔴 contested.
3. Every citation is checked — mechanical layer (reachability, domain authority, field completeness, dedup) plus semantic layer (does the source actually support the claim?). Unverified references never masquerade as real.

⛔ Iron rules (zero exceptions)

1. Never fabricate: citations must come from pages actually fetched this session. Re-search rather than write URLs from memory.
2. Never pretend: unchecked references are marked unverified; fetch failures are unreachable (≠ nonexistent — flagged for human review).
3. Don't hide conflicts: when sources disagree, present the disagreement, mark 🔴, show each side's evidence.
4. Budgeted search: QUICK ≤6 searches, FULL ≤15. Out of budget → state the gaps honestly instead of forcing conclusions.
5. Calibrate before searching (FULL mode): scope / timeframe / audience / output format must be locked first.

Step 0: mode selection

One verifiable fact → QUICK. Synthesis or trade-offs → FULL. "Quick check" forces QUICK; "thorough" forces FULL. Unsure → FULL. Pre-submission bibliography final check skips this choice: --preset submission (one flag = strict + GB·T/BibTeX/CSV exports).

Five-phase workflow

1. CALIBRATE (FULL only)

Ask 3–5 high-leverage questions at once: scope, timeframe, audience/depth, output format, decision context. Never re-ask what the user provided; if they decline, proceed with stated defaults. Three rules: order questions by dependency; each carries a recommended answer phrased so "yes" accepts it; facts you can look up yourself never become questions — decisions stay with the user.

2. PLAN

Show a short plan: 3–7 sub-questions, source priority (primary/official > major media > community/blog as leads only), budget.

3. SEARCH (iterative)

Read references/search-strategies.md first. Each round targets one sub-question; evolve queries with discovered terms; search both English and Chinese when the topic spans both; fetch full text of the 2–5 most valuable sources (never conclude from snippets); verify key numbers on the original page before quoting.

4. VERIFY (the heart of this skill)

Register every reference in research_refs.json (schema in references/report-template.md), then run:

python scripts/verify_refs.py --refs research_refs.json --out verify_report.md
# Zotero/EndNote .bib feeds in directly:
python scripts/verify_refs.py --refs bibliography.bib --out report.md
# Big batch? Self-check first (zero outbound by default):
python scripts/verify_refs.py --doctor --net

Five verdicts: verified / partial / unreachable (needs_human_check) / invalid / unverified. Every identifier (url/doi/pmid/arxiv) is cross-checked against its official registry, so fabricated IDs are judged invalid — never silently unreachable. Every report opens with a BLUF dual-reader header + CiteScore (0-100 + A-D grade) + a one-line pre-submission conclusion.

Mechanical layer (the script)

Full semantics: references/verification-details.md.

Semantic layer (the model)

Decompose each cited claim into atomic claim-triplets (subject–relation–object) and verify each against the source; register the verdict structurally ("semantic": {"claim", "support", "quote", "note"}) — it becomes auditable workpaper; not_in_source/contradicted cap the mechanical verdict at partial — a source that exists is not a source that agrees.

Task → flag

5. SYNTHESIZE

Follow references/report-template.md: executive summary first; every key conclusion carries a confidence grade + citation ids; the reference table carries verdicts; unverified/unreachable live only in the "human review" section; finish with a finding ledger — revisit the plan's question list and mark each as answered / partially answered / unresolved (with the budget ledger: rounds used, remaining), then gaps, disagreements, follow-up questions.

Files

⚠️ Common mistakes

See references/anti-patterns.md (14 entries, each with the right way instead). The two that matter most: never treat verified as "the content is correct" — that is the semantic layer's job; never treat unreachable as "fake" — retry via --cn/--proxy first.

Security, honest limits, FAQ

• Security & behavior declaration: single-run; HTTPS-only to the official academic registries (doi.org / api.crossref.org / eutils.ncbi.nlm.nih.gov / export.arxiv.org / api.openalex.org / api.semanticscholar.org / archive.org / pubmed.ncbi.nlm.nih.gov); zero telemetry. Full text: references/security.md
• Honest limits & explicit non-goals: references/out-of-scope.md
• Common questions: references/faq.md

30-second quickstart

# 1. references as JSON (title/url/source/year) — or a Zotero .bib
# 2. verify:
python scripts/verify_refs.py --refs refs.json --out report.md
# 3. read report.md — CiteScore + pre-submission conclusion at the top.
# Paper? add --export bibtex.  Medical? add --profile medical.
# Already verified once? add --grill report.json for the review checklist.

Environment fallback

Without web tools: state honestly that only the "user-supplied material + mechanical verification" mode is possible; never pretend to search.