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 skills add zevtos/agentpipe --skill ultrasearchgit clone --depth 1 https://github.com/zevtos/agentpipeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zevtos/agentpipe/ultrasearch)<a href="https://agentmods.dev/skills/zevtos/agentpipe/ultrasearch"><img src="https://agentmods.dev/badge/skills/zevtos/agentpipe/ultrasearch.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00183 | $0.05403 |
| Opus 5 | $0.00092 | $0.02701 |
| Sonnet 5 | $0.00037 | $0.01081 |
| Haiku 4.5 | $0.00018 | $0.00540 |
Grade A, and why
ultrasearch 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 7d 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 — 327 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ultrasearch — thesis-level literature research
⛔ Rules that override everything else
- NEVER fabricate DOIs or citations. Every DOI in the final report MUST exist in
papers.doiofcorpus.db. A regex-validated check is in the Checklist section; run it before delivering output. - NEVER skip the env-var pre-flight.
OPENALEX_API_KEYandUNPAYWALL_EMAILare not optional. Failing fast on missing env vars is correct behavior, not a bug. - NEVER bypass the venv. Every script is invoked through
ensure_env.py, which resolves the skill's venv (a global state dir outside the code — ADR-008). Calling extract/index scripts with systempython3will fail —sentence-transformers,pymupdf4llm, andsqlite-veclive only in that venv. - NEVER deliver a report whose paragraphs lack
[Sn]citation markers.synthesize.validate_report()returns the offenders — fix or remove them. - NEVER delete
corpus.db. It is user content (ADR-008), stored in a global state dir outside the code; reinstall never touches it. If the user explicitly asks to reset, resolve the path as in Persistent corpus andrm "$DB"*.
Required environment variables
export OPENALEX_API_KEY="..." # free key — https://openalex.org/account
export OPENALEX_EMAIL="[email protected]" # polite-pool identifier
export UNPAYWALL_EMAIL="[email protected]" # mandatory for Tier 2 fetch
export S2_API_KEY="..." # optional — dedicated 1 RPS pool
# Stage 2 additions:
export CORE_API_KEY="..." # optional — enables CORE source (5 of 6 work without)
export ZOTERO_API_KEY="..." # optional — enables --export-zotero remote push
export ZOTERO_USER_ID="..." # required if ZOTERO_API_KEY set
| Var | Required? | What breaks without it |
|---|---|---|
OPENALEX_API_KEY |
YES (post 13 Feb 2026) | OpenAlex returns 401 for new users |
OPENALEX_EMAIL |
Recommended | drops to anonymous quota |
UNPAYWALL_EMAIL |
YES | Tier 2 (Unpaywall PDF lookup) skipped; cascade loses ~30% recall |
S2_API_KEY |
Optional | shares anonymous 5000/5min bucket; traversal hits it harder |
CORE_API_KEY |
Optional (Stage 2) | CORE source disabled; other 5 sources cover |
ZOTERO_API_KEY |
Optional (Stage 2) | --export-zotero writes .bib only, no remote push |
ZOTERO_USER_ID |
Required if ZOTERO_API_KEY set | API push fails fast |
What ships with it
59 files 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.
- classifier.md 5.3 KB
- data/.gitignore 98 B
- data/.gitkeep 0 B
- data/README.md 1.9 KB
- data/schema.sql 16 KB
- LICENSE 1.0 KB
- profiles/_schema.json 4.6 KB
- profiles/academic.yaml 1.1 KB
- profiles/dev.yaml 1.2 KB
- profiles/docs.yaml 1.2 KB
- prompts/critic.txt 7.8 KB
- prompts/perspective-questions.txt 1.4 KB
- prompts/polisher.txt 3.1 KB
- prompts/rcs-summary.txt 2.7 KB
- prompts/section-writer.txt 2.0 KB
- README.md 2.1 KB
- references/apis.md 5.0 KB
- references/methodology.md 6.7 KB
- references/parsing-troubleshooting.md 4.5 KB
- references/ru-sources.md 5.0 KB
- scripts/_common.py 10 KB runs code
- scripts/_profile.py 12 KB runs code
- scripts/classifier.py 15 KB runs code
- scripts/crawl/__init__.py 7.0 KB runs code
- scripts/crawl/crawl4ai_helpers.py 2.5 KB runs code
- scripts/crawl/llms_txt.py 1.2 KB runs code
- scripts/crawl/sitemap.py 1.4 KB runs code
- scripts/discover.py 30 KB runs code
- scripts/ensure_env.py 15 KB runs code
- scripts/fetch.py 16 KB runs code
- scripts/index.py 22 KB runs code
- scripts/orchestrate.py 6.7 KB runs code
- scripts/parse.py 15 KB runs code
- scripts/quality.py 15 KB runs code
- scripts/render_graph.py 4.7 KB runs code
- scripts/requirements.txt 3.6 KB
- scripts/retrieve.py 11 KB runs code
- scripts/scoring/__init__.py 2.3 KB runs code
- scripts/scoring/academic.py 1.9 KB runs code
- scripts/scoring/dev.py 5.4 KB runs code
- scripts/scoring/docs.py 1.7 KB runs code
- scripts/sources/__init__.py 1.8 KB runs code
- scripts/sources/_base.py 3.2 KB runs code
- scripts/sources/deps_dev.py 3.4 KB runs code
- scripts/sources/docs_crawl.py 3.6 KB runs code
- scripts/sources/github.py 5.4 KB runs code
- scripts/sources/hn.py 2.9 KB runs code
- scripts/sources/pypi.py 3.3 KB runs code
- scripts/sources/stackex.py 4.9 KB runs code
- scripts/synthesize_v2.py 3.4 KB runs code
- scripts/synthesize.py 11 KB runs code
- scripts/templates/__init__.py 1.8 KB runs code
- scripts/translate.py 10 KB runs code
- scripts/traverse.py 22 KB runs code
- scripts/ultrasearch.py 28 KB runs code
- scripts/zotero.py 9.9 KB runs code
- templates/adr.md.j2 1.8 KB
- templates/library_matrix.md.j2 1.5 KB
- templates/literature_review.md.j2 888 B
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.
- 7d ago First seen · 327 lines · 183 tokens per session scan A 6a8f752a1fd7
ultrasearch is a skill published in the GitHub repository zevtos/agentpipe (11 stars, last pushed 2mo ago), licensed MIT. It adds 183 tokens to every session and 5,403 once invoked, about $0.0009 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
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
exploratory-data-analysis
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
phylogenetics
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
mapping-to-snomed
Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…