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Track Experiment Locally

encode_track_experiment
Idempotent

Save an ENCODE experiment to a local library with its publications, methods, and pipeline info. Track metadata and associated research for later comparison and citation.

Instructions

Track an ENCODE experiment locally with its publications, methods, and pipeline info.

Fetches full experiment metadata from ENCODE and stores it in a local SQLite database along with any associated publications (PMIDs, DOIs, authors, journal) and pipeline/analysis information (software versions, methods).

This is like adding an experiment to your "library" - similar to Endnote for papers.

WHEN TO USE: Use to save an experiment to your local library with publications and pipeline info. Required before compare or citations. RELATED TOOLS: encode_compare_experiments, encode_get_citations, encode_export_data

Args: accession: ENCODE experiment accession (e.g., "ENCSR133RZO") fetch_publications: Also fetch and store publications/citations (default True) fetch_pipelines: Also fetch and store pipeline/analysis info (default True) notes: Optional notes to attach to this experiment

Returns: JSON with tracking result including publications and pipeline info found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accessionYes
fetch_publicationsNo
fetch_pipelinesNo
notesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses that the tool fetches external data, stores in a local SQLite database, and associates publications and pipeline info. Annotations already indicate idempotency and open-world behavior, so the description adds useful context without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with a clear first sentence, metaphor, usage guidelines, and parameter list. While slightly verbose, every section adds value. Could be more concise but still effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema and annotations, the description covers the main functionality and use case. Minor omission: no mention of error handling for invalid accessions, but overall sufficient for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates by explaining each parameter: accession (example), fetch_publications (default true), fetch_pipelines (default true), and notes (optional). This adds meaning beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('track') and the resource ('experiment'), specifying that it stores metadata locally with publications and pipeline info. It distinguishes itself from siblings by explaining its unique role as a prerequisite for comparison and citation tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit 'WHEN TO USE' guidance, stating it is required before using compare or citations. It also lists related sibling tools, helping the agent choose correctly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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