Evidence map›Paper›PMID 42647176›Full record

ArticleBioinformatics (Oxford, England)2026

Coala: a standard-based framework for converting CWL-described command-line tools into agentic toolsets.

Qiang Hu, Qianqian Zhu, Hong Zhang, Tao Liu, Song Liu

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Qiang HuDepartment of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, United States.ORCID 0000-0002-4090-5539
Qianqian ZhuDepartment of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, United States.
Hong ZhangDepartment of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, United States.
Tao LiuDepartment of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, United States.ORCID 0000-0002-8818-8313
Song LiuDepartment of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, United States.ORCID 0000-0001-6351-2941

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

summaryLarge Language Models (LLM) can orchestrate computational analyses through agentic systems, but scaling their toolsets remains a barrier because tool definitions are often hard coded into agent implementation. We developed Command-line LLM-agent Adapter (Coala), a standard-based framework that bridges the Model Context Protocol (MCP) and the Common Workflow Language (CWL). Coala turns CWL tool descriptions into MCP-compatible, LLM-accessible schemas, treating tool definitions as data rather than code. Tools are then executed in containerized environments through a generic MCP server, which separates the agent's reasoning from tool execution. This framework improves reproducibility, reduces ongoing maintenance burden, and enables interactive access to local command-line tools through natural-language queries. AVAILABILITY AND IMPLEMENTATION: Coala is available at https://coala.info and is openly developed on GitHub: https://github.com/coala-info/coala.

Indexed as

Computational BiologySoftwareLarge Language ModelsWorkflow

Identifiers

PMID42647176
PMCPMC13549935

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.