grounded-citations – skill Dữ liệu & Khoa học cho agent AI
Neo câu trả lời và tài liệu vào các nguồn có trích dẫn, có thể kiểm chứng.
Cài skill grounded-citations bằng một lệnh
Chọn công cụ bạn đang dùng, copy lệnh và dán vào terminal. Skill sẽ nằm trong thư mục skills của công cụ đó và sẵn sàng dùng ở phiên làm việc tiếp theo.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/grounded-citations-572ab.tgz | tar xz -C ~/.claude/skills
Gọi trong Claude Code: /grounded-citations – rồi mô tả công việc bạn muốn làm.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/grounded-citations-572ab.tgz | tar xz -C ~/.codex/skills
Gọi trong Codex: $grounded-citations – rồi mô tả công việc bạn muốn làm.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/grounded-citations-572ab.tgz | tar xz -C ~/.hermes/skills
Gọi trong Hermes Agent: /grounded-citations – rồi mô tả công việc bạn muốn làm.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/grounded-citations-572ab.tgz | tar xz -C ~/.deepcode/skills
Gọi trong DeepSeek: /grounded-citations – rồi mô tả công việc bạn muốn làm.
Nội dung SKILL.md
Nội dung SKILL.md gốc bằng tiếng Anh.
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_exec, 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 citationsadd 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
| Action | Command |
|---|---|
| Fresh ledger for a new task | sources.py reset |
| Register a source, get its id | sources.py add <url> [--title T] |
| Register several at once | sources.py add <url1> <url2> ... |
| Register from JSON tool output | sources.py ingest results.json |
| Attach verbatim evidence to a source | sources.py quote <id> --text "exact wording" --from page.txt |
| Show ledger | sources.py list [--json] |
| Render the Sources block | sources.py render [--style markdown\|plain\|footnotes\|bibtex\|evidence] [--only 1,3] |
| Render only what a draft cites | sources.py render --cited-in draft.md |
| Rewrite a draft's Sources block in place | sources.py render --replace-in draft.md |
| Check a draft's citations | sources.py verify draft.md [--strict] [--min-coverage 0.6] [--evidence] |
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_exec / 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:
| Source type | Route | What it adds |
|---|---|---|
| Open web | web_search → web_extract | official docs, articles, announcements |
| Community discussion | reddit-reading (search, thread) | real user experience, complaints, workarounds |
| Blogs / releases / changelogs | rss-feeds (read, discover) | dated primary posts, version history |
| Video | youtube-content | walkthroughs, demos, talks |
| Code | terminal with gh search repos / gh search issues | implementations, open bugs |
| X/Twitter | xurl (needs API access) | announcements, developer chatter |
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.
Fact-Checking Mode
For work where the reader must be able to check the chain — medical, legal,
financial, safety, disputed claims, or when the user asks for fact-checking —
upgrade from citations to evidence:
① Attach a verbatim quote per source. After extracting a page, save its
text to a file and attach the sentence(s) that carry each claim:
python "$S" quote 1 --text "Ice is about 9% less dense than liquid water." --from page1.txtThe quote is rejected unless it appears verbatim in the evidence text
(insensitive to whitespace, case, and markdown markup — inline links like
_[ERAP1](https://…)_ in extracted text match the plain prose a reader sees),
so a paraphrase or misremembered figure cannot masquerade as evidence.
Copy-paste from the fetched text; never retype. Quote the sentence as the
reader sees it — the matcher sees through the extractor's markup for you, so
you don't have to reproduce link syntax or escaped asterisks in your quote.
② Flag model-knowledge claims with [unverified]. A load-bearing claim
you could not source gets an explicit marker instead of a citation:
The refactor likely predates the 2.0 release.[unverified]verify --min-coverage counts [unverified] sentences as covered — the goal
is declared provenance for every claim, not a citation on every sentence.
If a key claim can be checked, check it; [unverified] is for what genuinely
cannot be, and a fact-check deliverable dominated by [unverified] markers
should say so in its summary.
③ Cross-check disputed facts against a second independent source. When two
sources disagree, cite both readings with their own ids and quotes, and say
which you weight and why. One source is reporting; two independent sources are
corroboration.
④ Verify with the evidence gate and render the evidence block:
python "$S" verify report.md --evidence --min-coverage 0.5
python "$S" render --style evidence --replace-in report.md--evidence fails the draft if any cited source has no attached quote. The
evidence render style prints each source's quotes beneath its U
… (nội dung đầy đủ có trong gói tải về)
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