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Glama

BagIQ MCP

recommend_bag_fillers

Suggests the highest-rated discs to fill missing shot slots or close voids in the bag based on BagIQ matrix coordinates and DiscList ratings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brandNoOptional brand filter for recommendations
discsYesCurrent bag contents
limitNoNumber of recommendations per gap (1..5, default 3)
gap_idNoSpecific gap ID to fill (e.g. 'fairway-understable', 'approach-overstable', 'mid-neutral')

Schema Changelog

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

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context by stating the recommendation is based on 'BagIQ matrix coordinates and DiscList ratings,' which explains the underlying logic. However, it does not explicitly state that the operation is read-only, nor does it mention potential edge cases like empty recommendations or handling of locked discs. The description provides some transparency but not a comprehensive behavioral profile.

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 sentence that front-loads the primary action and resource. Every word earns its place, with no fluff or repetition. It is concise and efficient.

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

Completeness2/5

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

Given the tool's moderate complexity (4 parameters, no annotations, no output schema), the description is incomplete. It does not explain the return format or what happens when no gaps exist, nor does it provide any usage guidance relative to sibling tools. The agent is left without information on how to interpret the results or decide when to use this tool instead of find_bag_gaps or build_minimal_bag. The description is too minimal for a tool that likely requires more contextual cues.

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?

The schema description coverage is 100%, meaning all four parameters are already documented in the schema. The description adds no additional meaning to the parameters; it mentions 'BagIQ matrix coordinates' but that is not a parameter. Per the calibration, a baseline of 3 is appropriate when the schema fully covers parameters and the description adds no extra value.

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

Purpose4/5

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

The description clearly states the action ('Suggests the highest-rated discs') and the resource ('to fill missing shot slots or close voids in the bag'). It is specific and distinguishes the tool's purpose from general bag analysis. However, it does not explicitly name any sibling tool to differentiate from, so it stops short of a 5.

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 when to use the tool (when there are gaps or voids in the bag) but provides no explicit guidance on when not to use it or how it compares to alternatives like find_bag_gaps or analyze_bag. The usage context is clear but no exclusions or alternatives are given.

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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