polars-dovmed
Skill9 starsChanged 4 months agoMITView on GitHub
Run structured full-text searches of PMC Open Access and bioRxiv with polars-dovmed. Use for reproducible literature searches through the hosted API or local parquet corpora.
- Reads credentials
In this repository35 other files it gives its agents.
- AGENTS.mdAGENTS.md
- docs/agents.mdAGENTS.md
- ai-scientist-evaluatorSkill
- arxiv-searchSkill
- beautiful-data-vizSkill
- bio-annotationSkill
- bio-assembly-qcSkill
- bio-binning-qcSkill
- bio-fasta-database-curatorSkill
- bio-foundation-housekeepingSkill
- bio-gene-callingSkill
- bioinformatics-projectSkill
- bio-interdomain-hgtSkill
- bio-logicSkill
- bio-phylogenomicsSkill
- bio-prefect-dask-nextflowSkill
- bio-protein-clustering-pangenomeSkill
- bio-reads-qc-mappingSkill
- biorxiv-searchSkill
- bio-stats-ml-reportingSkill
- bio-structure-annotationSkill
- bio-viromicsSkill
- bio-workflow-methods-docwriterSkill
- crossref-lookupSkill
- csag-extractionSkill
- exploratory-data-analysisSkill
- manuscript-review-councilSkill
- notebooksSkill
- pdf-to-mdSkill
- plotly-dashboard-skillSkill
- proposal-reviewSkill
- public-db-lookupSkill
- scientific-impact-assessmentSkill
- scientific-writingSkill
- tracking-taxonomy-updatesSkill
The file
We split this skill into the rules it gives an agent
12 rules. About 0 are common, 2 are distinctive, and 10 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
10
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 9
Search the PubMed Central Open Access and bioRxiv corpora with polars-dovmed, through the hosted API or local parquet files.
- Very specific: line 21
Create a run directory, tasks/polars-dovmed-runs/<date-topic>/, outside $SKILL_DIR.
- Very specific: line 22
Write query.json (format below) and inspect it before searching: spelling, taxonomy aliases, regex escaping, and noisy terms.
- Distinctive: line 24
Do not invent aliases by splitting compact taxon, gene, or clade names.
- Very specific: line 25
Put acronym collisions and wrong systems in disqualifying_terms.
- Very specific: line 26
Run discovery first, one corpus per call.
- Very specific: line 29
Use --extract-matches none --add-group-counts primary for discovery.
- Very specific: line 33
When speed matters, record wall time with shell time -p or timeout, plus the helper's elapsed_ms.
- Very specific: line 34
Do not use the flat /api/search_literature endpoint.
- Distinctive: line 116
Run either check before declaring an outage.
- Very specific: line 145
Solution: Run --corpus biorxiv and --corpus pmc separately and merge the results.
- Very specific: line 160
Solution: Use shell time -p or record start and end timestamps.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
polars-dovmed
Search the PubMed Central Open Access and bioRxiv corpora with polars-dovmed, through the hosted API or local parquet files.
SKILL_DIR is the directory that contains this SKILL.md, installed at ~/.agents/skills/polars-dovmed. Run the helper as uv run --script "$SKILL_DIR/scripts/query_literature.py" so its pinned dependency is available. The helper loads ~/.config/polars-dovmed/.env.
Access
- Hosted API: needs
POLARS_DOVMED_API_KEYin the environment or in the.envfile. Never pass the key in argv, and never write it to run directories, memory records, summaries, or answers. The API root (https://api.newlineages.com/) states that keys are issued by the admin only. - Local corpora: upstream
dovmed download,dovmed build-parquet, anddovmed scanfrom https://github.com/UriNeri/polars-dovmed.omics-skillsships neither an API key nor the corpora. - With neither, state that
polars-dovmedis not configured and use another literature skill.
Instructions
- Create a run directory,
tasks/polars-dovmed-runs/<date-topic>/, outside$SKILL_DIR. Saveprompt.txt,query.json, payloads, raw responses, timing files, and any curated summary there. Do not commit generated runs. - Write
query.json(format below) and inspect it before searching: spelling, taxonomy aliases, regex escaping, and noisy terms.- Start anchor-only: exact entity names and evidence-based aliases. For prompts such as "hosts of X" or "distribution and genomics of X", search X and its aliases first and use the topic words for triage or a second pass. Never add generic words (distribution, genome, environment, host, taxonomy) as peer OR concepts.
- Do not invent aliases by splitting compact taxon, gene, or clade names. Keep a real multi-word synonym as one phrase term.
- Put acronym collisions and wrong systems in
disqualifying_terms.
- Run discovery first, one corpus per call. Never start with
--corpus both.- bioRxiv: async discovery with
--poll-timeout 75and--details-rerank-limit8 to 12. - OpenPMC:
--sync --year-bands clean_split --year-band-workers 4 --skip-details-rerank --poll-timeout 120. Map a requested year range to its bands and search only those (table below). Never run a broad unbanded OpenPMC scan. Fetch details by PMCID after inspecting the top hits. - Use
--extract-matches none --add-group-counts primaryfor discovery. - Wrap calls in
timeoutwhen it exists.
- bioRxiv: async discovery with
- Inspect the first 5 to 10 hits. If they are noisy, refine
query.jsonand rerun. - Fill citation metadata from the corpus details first, then from
--crossref-metadataor/crossref-lookup. Use DOI landing pages only when corpus metadata and Crossref disagree or stay ambiguous; do not use generic web search for DOI repair. - When speed matters, record wall time with shell
time -portimeout, plus the helper'selapsed_ms. Timeouts and failed endpoints are results; report them. - Do not use the flat
/api/search_literatureendpoint. It needs--allow-flat-queryand can hang behind the edge proxy.
Query JSON
{
"anchor_entity": [["primary_name"], ["alias_1"], ["alias_2"]],
"relation_or_property": [["primary_name", "relation_term"]],
"disqualifying_terms": [["term_to_exclude"]]
}Both search paths (FTS and parquet scan) apply the same logic: terms in one inner group are AND'd and must co-occur; inner groups in a concept are OR'd; concepts are OR'd, and items matching more groups rank higher. A multi-word term matches as an exact phrase. List each synonym as its own single-term group; use a multi-term group only to require co-occurrence.
Rank hits in this order: anchor in title, anchor in abstract, anchor plus support term in title or abstract, several distinct group matches, full-text-only matches. Down-rank hits that match only generic support terms.
Year bands (OpenPMC)
| Requested years | --year-bands value |
| 2009 and earlier | pre_2010 |
| 2010 to 2020 | 2010_2020 |
| 2021 to 2023 | 2021_2023 |
| 2024 and later | 2024_plus |
| No constraint | clean_split (all four) |
For a range that crosses bands, pass a comma list, for example --year-bands 2021_2023,2024_plus.
Hosted API commands
RUN=tasks/polars-dovmed-runs/mirusviricota-hosts-$(date +%Y%m%d)
mkdir -p "$RUN"
printf '%s\n' "papers describing hosts of Mirusviricota" > "$RUN/prompt.txt"
# Write and inspect "$RUN/query.json" before searching.
# bioRxiv discovery
timeout 90s uv run --script "$SKILL_DIR/scripts/query_literature.py" \
--queries-file "$RUN/query.json" --corpus biorxiv --mode discovery \
--extract-matches none --add-group-counts primary \
--max-results 25 --details-rerank-limit 12 --poll-timeout 75 \
--save-payload "$RUN/payload_biorxiv.json" --save-response "$RUN/results_biorxiv.json" \
> "$RUN/summary_biorxiv.json" 2> "$RUN/time_biorxiv.txt"
# OpenPMC discovery over the four clean year bands
timeout 120s uv run --script "$SKILL_DIR/scripts/query_literature.py" \
--queries-file "$RUN/query.json" --corpus pmc --mode discovery \
--sync --year-bands clean_split --year-band-workers 4 --skip-details-rerank \
--extract-matches none --add-group-counts primary \
--max-results 25 --poll-timeout 120 \
--save-payload "$RUN/payload_pmc.json" --save-response "$RUN/results_pmc.json" \
> "$RUN/summary_pmc.json" 2> "$RUN/time_pmc.txt"
# Details for known PMCIDs (bioRxiv: pass DOIs with --corpus biorxiv),
# with bounded Crossref fill-in for missing DOI, year, or journal
uv run --script "$SKILL_DIR/scripts/query_literature.py" \
--details PMC6362216 PMC10132079 --corpus pmc \
--crossref-metadata --crossref-limit 10 \
--save-payload "$RUN/payload_details.json" --save-response "$RUN/results_details.json"Local commands
uv run --script "$SKILL_DIR/scripts/query_literature.py" \
--execution-mode local --corpus pmc \
--local-parquet-pattern "$DOVMED_PMC_PARQUET" \
--queries-file "$RUN/query.json" \
--save-payload "$RUN/payload_local.json" --save-response "$RUN/results_local.json"--corpus pmcreadsDOVMED_PMC_PARQUETand--corpus biorxivreadsDOVMED_BIORXIV_PARQUETunless--local-parquet-patternis given.--corpus bothneeds one compatible explicit pattern; otherwise run separate scans.- Local runs record
--corpus-revision(orDOVMED_CORPUS_REVISION) and readflattened.csv, falling back toprocessed.parquet(or the legacyprcoessed.parquet) only when the compact output is absent.--timeoutcaps a local scan (default 900 seconds).
Reachability and smoke check
curl -sS --max-time 20 https://api.newlineages.com/ returns service metadata. It proves the service is reachable, not that a corpus scan works. The smoke check runs one bounded bioRxiv discovery and one details lookup:
uv run --script "$SKILL_DIR/scripts/smoke_test.py" --run-dir tasks/polars-dovmed-runs/smoke-testRun either check before declaring an outage.
Input Requirements
- A literature question, turned into an inspected
query.json. - A hosted API key or local parquet files for the requested corpus.
- A writable run directory outside
$SKILL_DIR.
Output
prompt.txt,query.json, payload JSON, raw response JSON, timing files, and an optional curated summary in the run directory.- A paper list with titles, identifiers, corpus, relevance notes, and timing.
- Warnings for timeouts, HTTP 502,
Database not found, missing metadata, or fallback use.
Quality Gates
- The API key stayed in the environment and appears in no artifact.
- The run directory is outside
$SKILL_DIR. query.jsonwas written anchor-first and inspected before the search.- Each corpus ran as its own discovery call; OpenPMC used clean year bands with
--syncand--skip-details-rerank, limited to the requested years. - The flat endpoint,
--corpus both, and unbanded OpenPMC scans were avoided, or the reason is stated. - Every hosted call had a poll timeout and, where available, a wall-clock
timeout. - The first 5 to 10 hits were reviewed and noisy terms refined.
- Citation metadata came from corpus details, then bounded Crossref, not generic web search.
- Timings and failures are reported when speed is part of the request.
Troubleshooting
Issue: --corpus both returns HTTP 502.
Solution: Run --corpus biorxiv and --corpus pmc separately and merge the results.
Issue: OpenPMC year-band search returns Database not found.
Solution: Report that the deployment does not expose the indexed OpenPMC bands. Do not fall back to an unbanded scan.
Issue: OpenPMC year-band search times out. Solution: Report the timeout and keep the bioRxiv result. Narrow to the requested bands or refine the anchors; do not retry with longer waits or an unbanded scan.
Issue: A "topic of X" query returns generic topic papers. Solution: Rerun with the entity and its aliases only, and use topic terms during triage.
Issue: Raw urllib requests get HTTP 403 with Cloudflare error 1010.
Solution: Cloudflare rejects Python's default user agent. Use the helper, or send both X-API-Key and a User-Agent header.
Issue: /usr/bin/time is missing.
Solution: Use shell time -p or record start and end timestamps.
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