Grounded Citations

Grounded Citations

Every claim taken from an outside source gets an inline numbered citation and a Sources: list, Perplexity-style. A ledger script owns the url → [n] mapping so the numbers and URLs come from retrieval, never from memory — the model only ever emits small integers it was handed.

For high-stakes work the same ledger doubles as a fact-checking chain: verbatim quotes are attached to each source (rejected unless they literally appear in the fetched page text), claims from model knowledge are flagged [unverified], and verify --evidence fails any draft whose cited sources carry no evidence.

This skill covers answers in chat, written documents (markdown, PDF, docx, slides), and research reports. It does not cover academic BibTeX pipelines — for conference papers use the arxiv skill, which this skill feeds (see references/citation-formats.md).

When to Use

Use whenever an answer or artifact rests on information you fetched rather than knew:

• Research, comparisons, news summaries, "what is the current state of X"
• Any deliverable you write to disk that quotes, paraphrases, or reports outside facts — reports, briefs, docs, decks, wiki pages
• Fact-finding where the user will want to check your work
• Multi-source synthesis where conflicting sources must be attributed

Skip inline citations when the retrieval is incidental to another task — a quick syntax/version lookup mid-coding, casual conversation, creative writing. Mention a URL only if the user would plausibly want the link.

Prerequisites

None beyond the standard toolset. scripts/sources.py is stdlib-only Python 3. Retrieval comes from whatever is configured: web_search, web_extract, browser_navigate, or terminal (curl, CLIs).

Ledger location: $HERMES_HOME/cache/citations/ledger.json (profile-aware). Override per task with --ledger <path> or HERMES_CITATION_LEDGER.

How to Run

S=~/.hermes/skills/research/grounded-citations/scripts/sources.py

python "$S" reset                                  # start a clean ledger
python "$S" add https://example.com/a --title "A"  # prints: [1]
python "$S" add https://example.com/b --title "B"  # prints: [2]
python "$S" list                                   # ledger table
python "$S" render                                 # Sources: block
python "$S" verify draft.md                        # catch bad citations

add is idempotent and URL-normalized: the same page always returns the same id within a ledger, so ids stay stable across many search/extract rounds.

Quick Reference

Procedure

① Reset the ledger at the start of a task that will produce a grounded answer or document. Skip the reset when continuing work whose ids are already in a draft — reusing the ledger keeps the numbering stable.

② Register every source at retrieval time. After each web_search / web_extract / browser_navigate / fetch, pass the URLs to sources.py add (or pipe the raw JSON through sources.py ingest). Do this before writing prose. Registering later, from memory, is the failure mode this skill exists to prevent.

③ Write cite-while-drafting. Place the bracketed id(s) immediately after each sentence the source supports:

Ice floats because it is less dense than liquid water.[1][2]

• No space before the bracket; each id in its own brackets.
• Max 3 ids per sentence. Cite per sentence, not one dump at the end.
• Only ids the ledger returned. Never invent an id or a URL.
• Claims from your own knowledge get no citation.
• Conflicting sources: present both readings, each with its own id.
• Quote exact figures, dates, and names as the source states them; flag gaps explicitly ("no source found for X") instead of smoothing them over.

④ Append the Sources block with sources.py render --cited-in <draft> so the id → URL mapping is generated mechanically from the ledger, not retyped. For non-markdown targets pick the matching --style and follow references/citation-formats.md for placement (footnotes in docx, endnotes in PDF/LaTeX, a Sources slide in decks, per-page source lists in wiki output).

⑤ Verify before delivering — sources.py verify <draft> exits non-zero on unknown ids, on a Sources block that disagrees with the ledger, or (with --min-coverage) on prose that is too thinly cited. Fix and re-run.

⑥ Chat answers follow the same steps with the draft in your reply: register sources, cite inline, end with the rendered Sources: list. For a short answer you may render the block from sources.py render --only <ids> instead of writing to a file.

Multi-Platform Sweeps

"What are people saying about X" / "research X across the web" is not one web_search. Fan out across source types, collect in parallel, then synthesise with every claim attributed to the platform it came from:

The reddit-reading and rss-feeds skills are optional. If absent, install with hermes skills install official/social-media/reddit-reading or hermes skills install official/research/rss-feeds before using them.

Register every URL from every route in the ledger as it arrives (step ②). Keep opinion and measurement apart: a Reddit thread is evidence that users report something, not that it is true; pair it with a primary source or label it as sentiment. Report per-platform coverage gaps ("Reddit search returned nothing newer than March") rather than silently narrowing to what worked.