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- Aditya232-rtx/Ouroboros
- 최근 소스 활동
- 2026년 8월 22일 22:16
- 감지된 SKILL.md 언어
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/Aditya232-rtx/Ouroboros --skill grounded-citations명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Add security scanning to CI/CD with Fang — GitHub Actions, GitLab CI, or any pipeline — so every pull request gets a diff-scoped AI pentest that blocks vulnerable code before it merges, with results as PR comments and SARIF uploaded to code scanning. Covers both the self-hosted open-source CLI (runs in your runner) and the managed app.fang.ai platform (GitHub/GitLab app or API, no runner infra). Use when the user asks to add security scanning, SAST/DAST, pentesting, vulnerability checks, or automated security review to their CI pipeline, pre-merge gate, or PR workflow.
Fix security vulnerabilities found by a Fang pentest (open-source CLI or app.fang.ai cloud) — triage by severity, patch the root cause rather than the symptom, and re-run Fang to prove each fix actually closes the exploit. Handles injection, XSS, SSRF, broken access control, IDOR, and other validated findings. Use after a Fang scan reports findings, or when the user asks to remediate, patch, or fix security issues from a fang_runs report, vulnerabilities.json, findings.sarif, or a cloud scan.
Run a managed pentest of a web app or API through the app.fang.ai REST API — no local Docker, LLM key, or install needed. Create an API token, register domain/repository assets, launch and poll scans, triage vulnerabilities, export SARIF, download PDF/DOCX pentest reports for SOC 2 and other compliance evidence (Enterprise plan), start PR reviews, and set up schedules and webhooks. Use when the user wants continuous or scheduled pentesting-as-a-service, an auditor-ready pentest report, scans tracked in a team dashboard, or security testing from a sandboxed agent/CI environment with no infrastructure.
SKILL.md 표시 중
| name | grounded-citations |
| description | Ground answers and documents in cited, verifiable sources. |
| version | 1.1.0 |
| author | Ouro + Teknium |
| license | MIT |
| platforms | ["linux","macos","windows"] |
| metadata | {"hermes":{"tags":["Research","Citations","Grounding","Sources","Web","Reports"],"category":"research","related_skills":["research-paper-writing","arxiv","ocr-and-documents"]}} |
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 research-paper-writing skill, which this skill
feeds (see references/citation-formats.md).
Use whenever an answer or artifact rests on information you fetched rather than knew:
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.
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: $OURO_HOME/cache/citations/ledger.json (profile-aware).
Override per task with --ledger <path> or OURO_CITATION_LEDGER.
S=~/.ouro/skills/research/grounded-citations/scripts/sources.py
python "$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.
| 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] |
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]
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.
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.txt
The 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 URL, so the
deliverable shows claim → source → exact supporting text with nothing taken on
faith. Use --replace-in <draft> to rewrite an existing Sources block in place
(idempotent — safe to re-run after attaching more quotes); --cited-in prints
to stdout instead. Both emit the heading ## Sources (--style plain emits
Sources:).
What --min-coverage counts. Coverage is
sentences with declared provenance / prose sentences. A prose sentence is a
non-empty line fragment of 4+ words after the Sources block, headings (#),
table rows (|), and fenced code are dropped; blockquote markers are stripped.
Provenance is declared by either a [n] citation or an [unverified] marker,
so a sentence carrying both counts once. Run verify without a threshold first
and read the info: stats: line to see the counts before picking a number.
[4], [4] must stay that source. Run reset
only between tasks.render. A hand-typed URL
is an unverified claim.web_search
description supports only what it literally says. Cite the extracted page
when the claim needs the body — web_extract it first.--ledger (or OURO_CITATION_LEDGER) if their
outputs get merged, otherwise their ids will collide.web_extract
first, save the text, then quote --from that file.quote --text. The verbatim check will reject it; the
fix is to find the actual sentence, not to reword until something matches.[unverified] as an escape hatch. It marks the rare claim that
genuinely cannot be sourced; if most sentences carry it, the task needed more
retrieval, not more markers.render --replace-in <draft>; slicing
the file yourself risks a stale or duplicated block that verify then flags.python "$S" verify report.md --strict --min-coverage 0.5
Green means: every [n] in the draft exists in the ledger, the Sources block
lists exactly the cited ids with the ledger's URLs, and the cited share of
source-bearing sentences meets the threshold. Read the warnings even when the
exit code is 0 — uncited registered sources usually mean a claim lost its
attribution during editing.