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pathogen-variant-surveillance

Queries public GenSpectrum LAPIS data for pathogen genomic surveillance, current lineage nomenclature, weekly sequence proportions, reporting delays, and…

Skill by K-Dense-AI

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/k-dense-ai-pathogen-variant-surveillance

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About

Queries public GenSpectrum LAPIS data for pathogen genomic surveillance, current lineage nomenclature, weekly sequence proportions, reporting delays, and descriptive mutation frequencies. Use for variant surveillance, Pango lineage validation, dominant submitted lineages, Nextclade assignment provenance, SARS-CoV-2, influenza/H5N1 clades, RSV, mpox, measles, dengue, or LAPIS queries. Distinguishes sequence prevalence from infection prevalence, clades from genotypes, missing calls from reference matches, and sampling changes from biological growth advantage.

Use cases: data, marketing

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/pathogen-variant-surveillance

Tools it pre-approves 4

From allowed-tools in SKILL.md: the agent may use these without asking you each time.

  • Read
  • Write
  • Edit
  • Bash

What's inside

Skill name
pathogen-variant-surveillance
Description
Queries public GenSpectrum LAPIS data for pathogen genomic surveillance, current lineage nomenclature, weekly sequence proportions, reporting delays, and descriptive mutation frequencies. Use for variant surveillance, Pango lineage validation, dominant submitted lineages, Nextclade assignment provenance, SARS-CoV-2, influenza/H5N1 clades, RSV, mpox, measles, dengue, or LAPIS queries. Distinguishes sequence prevalence from infection prevalence, clades from genotypes, missing calls from reference matches, and sampling changes from biological growth advantage.
License
MIT
Compatibility
Requires Python 3.11+. Scripts use only the standard library. Needs network access to public LAPIS deployments on lapis.cov-spectrum.org, lapis.genspectrum.org, lapis.pathoplexus.org and raw.githubusercontent.com for pango-designation. No credentials for these public queries.
Allowed tools
Read, Write, Edit, Bash
Metadata
version: 1.3 · skill-author: K-Dense Inc. · last-reviewed: 2026-10-01
Instructions
173 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts
  • Pre-approves any shell command

Files (9)

  • SKILL.md
  • lapis-api.md · references/
  • lineage-nomenclature.md · references/
  • surveillance-caveats.md · references/
  • lapis_client.py · scripts/
  • lineage_prevalence.py · scripts/
  • mutation_profile.py · scripts/
  • reporting_lag.py · scripts/
  • resolve_lineage.py · scripts/

SKILL.md (first lines)

# Pathogen Variant Surveillance

## When to use

Use current data when a question depends on which lineages appear in submitted sequences,
what a lineage name currently means, or how the submitted sequence distribution changed.
Never answer a current circulation question from remembered lineage names or old examples.

This skill supports descriptive surveillance research. Counts describe sequences submitted to
one database under stated filters; they are not case counts, infection prevalence, clinical
interpretations, outbreak recommendations, or evidence of enhanced pathogen function.

## Verified scope

Reviewed on 2026-10-01 against official documentation, live schemas for all 15 registered
instances, and small public queries. SARS-CoV-2 served LAPIS 0.8.7/SILO 0.14.3; the other
registered deployments served LAPIS 0.8.0/SILO 0.11.0. Do not assume identical feature support.
Bundled standard-library scripts have synthetic regression tests and bounded live smoke checks.
Nextclade, GenoFLU, authenticated APIs, and sequence-level assay validation are not executed here.

| Instance | Host | Common lineage field |
| --- | --- | --- |
| `sars-cov-2` | lapis.cov-spectrum.org/open/v2 | `pangoLineage` (indexed) |
| `h5n1` | lapis.genspectrum.org/h5n1 | `clade` (unindexed) |
| `h3n2`, `h1n1pdm` | lapis.genspectrum.org/<name> | `cladeHA` / `cladeNA` (unindexed) |
| `influenza-a` | lapis.genspectrum.org/influenza-a | `subtypeHA` / `subtypeNA` |
| `rsv-a`, `rsv-b`, `mpox`, `measles`, `dengue`, `west-nile`, `hmpv`, `ebola-zaire`, `ebola-sudan`, `cchf` | lapis.pathoplexus.org/<name> | inspect the schema |

The scripts read `/sample/databaseConfig`. A lineage-index value is currently an identifier
string, not necessarily a boolean. Only indexed fields support descendant `NAME*` queries.
Use `--lineage-field` deliberately when several naming systems coexist. Unknown unindexed
values can return zero; that does not verify the name or prove biological absence.

When available, defaults select `versionStatus=LATEST_VERSION`, `isRevocation=false`, and
`dataUseTerms=OPEN`. These are printed with the result and can be overridden explicitly with
`--where`. Open access to an endpoint is not a blanket data-use license; preserve source
attribution and the applicable [Pathoplexus terms](https://pathoplexus.org/about/terms-of-use).

## Workflow

```bash
cd skills/pathogen-variant-surveillance/scripts
```

1. Inspect the instance and choose collection date, lineage system, geography, host and data
   inclusion rules. Country fields differ: SARS-CoV-2/GenSpectrum use `country`; Pathoplexus
   uses `geoLocCountry`. Inspect actual categories before choosing a value.
2. Review reporting delays before choosing the prevalence window.
3. Discover common labels in that window, then verify names in the relevant nomenclature.
4. Report counts, denominators, intervals, snapshot version, dates and exclusions together.

### Describe observed reporting delay

```bash
python3 reporting_lag.py --where country=USA --cohorts 6 --skip-months 3
```

This groups by **both collection and submission/release dates**, calculates each date difference,
and reports `mean_observed`, `min_observed`, `max_observed` and contributing cohort count.
It excludes missing dates, unequal collection-date range bounds, negative lags and submissions
after `--until`. Long offsets use only cohorts old enough to contribute that follow-up.

The result is a CDF conditional on records visible now. It cannot establish eventual completeness,
a trustworthy date, or when a record first appeared in LAPIS. `--until` sets an analysis anchor;
it does not retrieve an earlier database snapshot. Cohorts receive equal weight, not weight
proportional to sequence count. The contributing cohort set can vary by offset.

### Discover and describe weekly proportions

```bash
python3 lineage_prevalence.py --top 5 --where country=USA --weeks 12
```

Discovery ranks exact nonempty labels; `unassigned` remains a real category. The denominator
includes all selected records, including unassigned/null lineage calls. Overlapping descendant
queries must not be summed. Explicit lineage examples below illustrate syntax, not current dominance:

```bash
python3 lineage_prevalence.py "XFG*" --where country=USA --weeks 16 --growth --lag-days 90
```

Here `90` is an illustrative user-selected exclusion horizon, not a universal measured lag.
The window expands to whole ISO weeks and the output states the expanded dates. Weeks ending
within `--lag-days` of today, the current partial week, zero-count weeks, and weeks below the
chosen older-half count threshold are flagged `low`. Other weeks are not certified complete.
Growth fits exclude flagged weeks unless `--include-incomplete` is explicit.

For collection fields ending `RangeLower`, weekly and lag analyses require the corresponding
`RangeUpper` and exclude unequal bounds. The exclusion count covers returned records; date
range filters can already exclude null dates, so it is not a database-wide missing-date count.
Upstream imputation or inaccurate metadata cannot be detected from declared date types alone.

Proportions use Wilson intervals for binomial sampling uncertainty only. `--growth` fits a
weighted descriptive log-odds slope, with at least five observed sequences in three nonempty
weeks and dispersion floored at one. It is not transmissibility, fitness or a forecast.

### Verify current names

```bash
python3 resolve_lineage.py XFG PQ.17 PC.2 NOTALINEAGE --no-counts
```

Names here are input examples, not current claims. The resolver fetches Pango notes and alias
maps, reports withdrawals/redesignations, expands aliases, and reports indexed descendants.
Recombinant parentage comes from Pango alias lists; a LAPIS descendant tree need not encode it.
Only Pango inputs are case-normalized; other nomenclatures retain their original case.

Exit code 1 means at least one name is withdrawn, unknown, unverified, or its requested count
failed. Exit code 2 means a required source/query failed. An unindexed field without a naming
authority remains `unverified` even if sequences carry that label. Do not use a successful
count to claim an authoritative designation.

### Describe site-wise mutation frequencies

```bash
python3 mutation_profile.py "XFG*" --gene S --since 2026-01-01
python3 mutation_profile.py "XFG*" --versus "XFJ*" --gene S --since 2026-01-01
```

From K-Dense-AI/scientific-agent-skills, MIT.

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Stars
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Forks
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Open issues
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Last commit (this folder)
Oct 1, 2026 (1 month ago)
Last release
Oct 1, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
1.3
License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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pathogen-variant-surveillance skill. Agent Mart. https://agentmart.dev/skills/k-dense-ai-pathogen-variant-surveillance (last updated 2026-10-24)