Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ripemangobox/bite/papers-query-knowledge-basenpx skills add RipeMangoBox/BITE --skill papers-query-knowledge-basegit clone --depth 1 https://github.com/RipeMangoBox/BITEWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00091 | $0.01248 |
| Opus 5 | $0.00046 | $0.00624 |
| Sonnet 5 | $0.00018 | $0.00250 |
| Haiku 4.5 | $0.00009 | $0.00125 |
Grade A, and why
papers-query-knowledge-base scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Knowledge Base
Use this skill to query the local paper corpus across conversations and projects. The main evidence layer is obsidian-vault/analysis (analysis notes with TL;DR, semantic method/evidence sections, and PDF links). When it exists, obsidian-vault/index/index.jsonl is the fast filter layer for large vaults, while the Markdown pages in obsidian-vault/index/ remain useful for Obsidian jumps and backlink-friendly browsing.
Where the knowledge base lives: Under the current repository root that contains obsidian-vault/analysis/ and obsidian-vault/paperPDFs/. obsidian-vault/index/ is a generated companion layer created by papers-build-index.
Paths
- Use repo-relative paths rooted at the folder that contains
obsidian-vault/analysis/andobsidian-vault/paperPDFs/. - When invoking from another workspace, replace these with the correct absolute repository path for your machine.
Where things live
Relative to the repository root:
- Analysis notes:
obsidian-vault/analysis/<Topic>/<Venue_Year>/<Year>_<Title>.mdor flat venue folders such asobsidian-vault/analysis/ICLR_2026/<Title>.md; PDF path in frontmatterpdf_ref. - Generated index / navigation:
obsidian-vault/index/index.jsonl,obsidian-vault/index/paper_index.md,_AllPapers.md,by_topic/,by_method/,by_dataset/,by_venue_year/. - Public placeholder:
obsidian-vault/index/README.mdis tracked as a stable explanation file and is not overwritten by index generation.
All paths use forward slashes.
How to use for research
-
Find papers — Search
obsidian-vault/analysis/directly by title, task folder, tags, venue, year,core_operator, orprimary_logic. Ifobsidian-vault/index/index.jsonlis present, use it first to narrow a large candidate set, then read the matching notes for evidence. -
Read an analysis — Open the matched analysis note directly. Each note has: Frontmatter (title, venue, year, tags, aliases, pdf_ref, core_operator, primary_logic, claims; no
category,modalities, orfrontier); Quick Links & TL;DR; method/problem/evidence sections such as问题与动机,整体框架,核心模块与公式推导,实验与分析, and局限性与启发; and Local Reading (PDF). Older notes may still use legacy mixed headings, so match semantically rather than by one exact title string.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 76 lines · 91 tokens per session scan A dd33f0812a8c
papers-query-knowledge-base is a skill published in the GitHub repository RipeMangoBox/BITE (60 stars, last pushed 20d ago), licensed MIT. It adds 91 tokens to every session and 1,248 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
compile-wiki
Merge source summaries into durable concept pages with backlinks, index entries, and explicit open questions.
ingest-sources
Review newly ingested raw sources and draft or update source summary notes in notes/Sources/.
qa-agent
Answer questions from the vault, then file durable insights back into the knowledge base.
research-workflow
Manage resumable research runs under research/ and coordinate the collect, review, report, import, and archive steps.
lint-heal
Scan the vault for contradictions, unsupported claims, structural weaknesses, and missing pages, then repair what is safe.
render-output
Convert vault content into downstream outputs like memos, reports, slide outlines, diagrams, and plot specifications.