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 thesecondfox/skill --skill bio-database-access-batch-downloadsgit clone --depth 1 https://github.com/thesecondfox/skillWrote 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/thesecondfox/skill/bio-database-access-batch-downloads)<a href="https://agentmods.dev/skills/thesecondfox/skill/bio-database-access-batch-downloads"><img src="https://agentmods.dev/badge/skills/thesecondfox/skill/bio-database-access-batch-downloads/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/thesecondfox/skill/bio-database-access-batch-downloads"><img src="https://agentmods.dev/badge/skills/thesecondfox/skill/bio-database-access-batch-downloads.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 | $0.00042 | $0.02940 |
| Opus 5.5 | $0.00017 | $0.01176 |
| Sonnet 5.5 | $0.00008 | $0.00588 |
| Haiku 4.5 | $0.00004 | $0.00294 |
Grade A, and why
bio-batch-downloads scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
from urllib.error import HTTPError How it starts
The opening of the file, as written. The whole thing — 382 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: BioPython 1.83+, Entrez Direct 21.0+
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function)to check signatures
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Batch Downloads
"Download thousands of sequences from NCBI" → Search NCBI with history server, then batch-fetch results with rate limiting and retry logic.
- Python:
Entrez.esearch(),Entrez.efetch()withusehistory='y'(BioPython)
Download large numbers of records from NCBI efficiently using the history server, batching, and proper rate limiting.
Required Setup
from Bio import Entrez
import time
Entrez.email = '[email protected]' # Required by NCBI
Entrez.api_key = 'your_api_key' # Recommended for large downloads
Rate Limits
| Authentication | Requests/Second | Delay Between |
|---|---|---|
| Email only | 3 | 0.34 seconds |
| Email + API key | 10 | 0.1 seconds |
Get an API key at: https://www.ncbi.nlm.nih.gov/account/settings/
History Server
The history server stores search results on NCBI servers, enabling efficient batch retrieval without re-sending large ID lists.
How It Works
- Search with
usehistory='y' - Get
WebEnv(session ID) andquery_key(result set ID) - Fetch results in batches using these identifiers
- Results stay available for ~15 minutes
# Search with history
handle = Entrez.esearch(db='nucleotide', term='human[orgn] AND mRNA[fkey]', usehistory='y')
search = Entrez.read(handle)
handle.close()
webenv = search['WebEnv']
query_key = search['QueryKey']
total = int(search['Count'])
print(f"Found {total} records, stored in history")
Core Pattern: Batch Download
Goal: Download all records matching a search query, handling NCBI rate limits and large result sets.
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.
- 1mo ago First seen · 382 lines · 42 tokens per session scan A 5d19e3d39bc2
bio-batch-downloads is a skill published in the GitHub repository thesecondfox/skill (3 stars, last pushed 6mo ago), licensed MIT. It adds 42 tokens to every session and 2,940 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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