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 gkanogiannis/Gigwa-MCP --skill gigwa-region-scangit clone --depth 1 https://github.com/gkanogiannis/Gigwa-MCPWrote 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/gkanogiannis/gigwa-mcp/gigwa-region-scan)<a href="https://agentmods.dev/skills/gkanogiannis/gigwa-mcp/gigwa-region-scan"><img src="https://agentmods.dev/badge/skills/gkanogiannis/gigwa-mcp/gigwa-region-scan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gkanogiannis/gigwa-mcp/gigwa-region-scan"><img src="https://agentmods.dev/badge/skills/gkanogiannis/gigwa-mcp/gigwa-region-scan.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00217 | $0.01182 |
| Opus 5.5 | $0.00087 | $0.00473 |
| Sonnet 5.5 | $0.00043 | $0.00236 |
| Haiku 4.5 | $0.00022 | $0.00118 |
Grade A, and why
gigwa-region-scan 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 2mo 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gigwa region scan
Overview
Zoom into one genomic window of a variant set and report its variant density, common vs
rare composition, and local diversity/quality. Drives the gigwa-mcp MCP server's search,
diversity and QC tools against a single region.
When to use
- A user names a chromosome/contig (
chr1) or a coordinate range (chr1:1000000-2000000) and wants to know what's there. - You need a
variant_set_db_id(MODULE§project§run) — fromlist_variant_sets()or the gigwa-explore-instance skill.
Region syntax — the two interfaces (important)
The tools take the interval two different ways. Get this right or the filters silently apply to the whole set:
| Tool(s) | How to pass the window |
|---|---|
count_variants, search_variants |
split into reference_name, start, end (there is no region param) |
diversity_summary, qc_call_rate |
one region string: "chrom" or "chrom:start-end" |
Mapping example for chr1:1000000-2000000:
- search/count →
reference_name="chr1", start=1000000, end=2000000 - diversity/QC →
region="chr1:1000000-2000000"
Coordinates are 1-based inclusive. A whole chromosome is reference_name="chr1" (no
start/end) or region="chr1".
Step-by-step workflow
- Validate the contig —
list_sequences(variant_set_db_id)to confirm the exactreference_nameexists (names must match the run's contigs). - Count —
count_variants(variant_set_db_id, reference_name, start, end)— total variants in the window.count_variants(variant_set_db_id, reference_name, start, end, min_maf=0.05)— again, restricted to common variants; the gap = rare/low-frequency variants.
- List —
search_variants(variant_set_db_id, reference_name, start, end)writes the matching variants tovariant_search.csv(respects the same MAF/missingness filters; capped bymax_variants=100000). - Characterise the window (note the
region=string form):diversity_summary(variant_set_db_id, region="chr1:1000000-2000000")qc_call_rate(variant_set_db_id, region="chr1:1000000-2000000")
- Report variant density (per bp / per window), common-vs-rare split, and local diversity/call-rate.
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.
- 2mo ago First seen · 83 lines · 217 tokens per session scan A 4324e166c890
gigwa-region-scan is a skill published in the GitHub repository gkanogiannis/Gigwa-MCP (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 217 tokens to every session and 1,182 once invoked, about $0.0009 per session on Opus 5.5. 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 2026-08-31.
gigwa-region-scan compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| gigwa-region-scangkanogiannis/Gigwa-MCP | Skill | 0 | 1mo ago | Apache-2.0 | A | 217 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | yesterday | Apache-2.0 | A | 123 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 6d ago | MIT | A | 44 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 6d ago | MIT | A | 83 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 6d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | today | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | today | Apache-2.0 | A | 205 | Claude Code |