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Glama

BagIQ MCP

build_minimal_bag

Extracts an optimal 3-to-5 disc minimalist setup from a larger bag, maximizing shot coverage while detailing necessary compromises.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
discsYesFull disc collection or bag
target_countNoTarget number of discs in the minimal bag (2..6, default 3)

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries full transparency responsibility. It indicates the tool 'extracts' and 'detailing necessary compromises,' which hints at output behavior but does not disclose side effects, constraints, or the fact that target_count range (2..6) differs from the stated '3-to-5.' No contradictions with annotations since none exist.

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 a single, well-structured sentence that efficiently communicates the action, input, output goal, and additional output characteristic (compromises). No fluff or redundancy.

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?

For a straightforward tool with two parameters and no output schema, the description provides sufficient context: it names the input (larger bag), the processing goal (maximize coverage), and output trait (detailing compromises). Minor gap: it doesn't explicitly mention that target_count overrides the default 3-5 range, but this is covered by the schema.

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

Parameters3/5

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

Schema provides 100% coverage with detailed descriptions for both discs (including nested object fields) and target_count (with range and default). The description adds no extra parameter-specific meaning, so baseline score of 3 applies per rubric.

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 tool's function: 'Extracts an optimal 3-to-5 disc minimalist setup from a larger bag' with explicit goals of 'maximizing shot coverage while detailing necessary compromises.' This distinguishes it from sibling analysis tools like analyze_bag or find_bag_gaps.

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

Usage Guidelines4/5

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

The description implies when to use it (to reduce a larger collection to a minimalist setup) but does not explicitly contrast it with siblings. However, the clear purpose and sibling names (analyze, detect, find, recommend) make the appropriate use context readily inferable.

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

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but analyze_bag already reports gaps and overlaps, making find_bag_gaps and detect_overlap partially redundant with it. The descriptions clarify scope enough that an agent can choose correctly.

Naming Consistency5/5

All tool names follow a consistent snake_case verb-first pattern: analyze, build, detect, find, recommend. No mixed conventions or vague naming.

Tool Count5/5

Five tools is well-scoped for a bag analysis server, covering the core workflow without unnecessary bloat. Each tool has a clear role in the analysis pipeline.

Completeness5/5

The server covers the full bag analysis lifecycle: overall assessment, gap identification, overlap detection, minimal bag optimization, and filler recommendations. No obvious missing operation or dead end for the stated purpose.

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