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Glama

Gdc

by io.github.pipeworx-io

Search Files

search_files
Read-onlyIdempotent

Search NCI GDC genomic data files by project and/or data category (e.g. "Transcriptome Profiling", "Simple Nucleotide Variation", "DNA Methylation"). Returns file_id, file_name, data category/type/format, access level and file size. Keyless, open-access metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoNumber of files to return (default 20).
project_idNoRestrict to a GDC project, e.g. "TCGA-BRCA".
data_categoryNoData category, e.g. "Transcriptome Profiling", "Simple Nucleotide Variation".

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "data_category": "Transcriptome Profiling",
+    "project_id": "TCGA-BRCA"
+  },
+  {
+    "data_category": "Simple Nucleotide Variation",
+    "project_id": "TARGET-AML",
+    "size": 30
+  }
+]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

The annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint) already indicate a safe, read-only, idempotent operation. The description adds valuable context by stating 'Keyless, open-access metadata,' which clarifies authentication requirements and access level. No contradictions with annotations.

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

Conciseness5/5

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

The description is extremely concise at two sentences. The first sentence front-loads the core purpose and parameters, the second lists output and key context. Every sentence is essential and no redundant information.

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

Completeness5/5

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

Given the tool's simplicity (3 parameters, all documented), no output schema, and comprehensive annotations, the description covers all necessary information: what it does, how to use it (via examples), what it returns, and access context. No gaps are present.

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

Parameters4/5

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

The input schema provides full descriptions for all three parameters (100% coverage). The description adds value by giving concrete examples of valid values (e.g., 'TCGA-BRCA', 'Transcriptome Profiling') and listing returned fields, which helps the agent understand parameter usage beyond schema types.

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 (Search), the resource (NCI GDC genomic data files), and the available filters (project and data category). It also lists the returned fields, making the tool's purpose unambiguous. This distinguishes it from siblings like 'search_cases' which search different entities.

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

Usage Guidelines3/5

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

The description implies usage for searching files by project or data category, and provides example categories. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention when not to use it. Usage guidance is implied but not explicit, which is adequate for a simple search tool.

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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TDQS

A4/5.0
Disambiguation4/5

Most tools have distinct purposes, but ask_pipeworx and ask_pipeworx_grounded overlap in routing (differ only in answer mode), and the multiple Polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_kalshi_spread) could cause confusion without careful reading of descriptions.

Naming Consistency3/5

Naming mix of verb-first (ask_pipeworx, compare_entities) and noun-first (entity_profile, recent_changes) patterns. Most use snake_case consistently, but the pattern is not uniform—some tools are commands, others are descriptors. Notable deviations like 'pipeworx_feedback' and 'pmc' are missing here but the sample shows inconsistency.

Tool Count3/5

30 tools is on the high side, but the server covers a broad domain (data lookup, betting, AI, genomics, memory). Some tools could be merged (e.g., ask_pipeworx and its grounded variant), and the betting subdomain feels over-instrumented. The count is borderline between appropriate and heavy.

Completeness3/5

The server provides a wide range of operations for its diverse domains, but gaps exist: the genomics tools only offer basic metadata search (no download/analysis), and the betting tools lack historical data or backtesting. It covers common patterns but with notable omissions for a cohesive experience.

Resources