Suggests the highest-rated discs to fill missing shot slots or close voids in the bag based on BagIQ matrix coordinates and DiscList ratings.
| Name | Required | Description | Default |
|---|---|---|---|
| brand | No | Optional brand filter for recommendations | |
| discs | Yes | Current bag contents | |
| limit | No | Number of recommendations per gap (1..5, default 3) | |
| gap_id | No | Specific gap ID to fill (e.g. 'fairway-understable', 'approach-overstable', 'mid-neutral') |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It does disclose the internal basis (BagIQ matrix coordinates and DiscList ratings) and the non-mutating word 'suggests,' but it does not state side-effect safety, output shape, or behavior when no gaps exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no wasted words. Every phrase ('highest-rated', 'BagIQ matrix coordinates', 'DiscList ratings') contributes information about what the tool does and how it computes recommendations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The schema covers parameters well, but with no output schema and no mention of sibling routing, an agent is left uncertain about the exact result format and when to prefer this over find_bag_gaps. It is minimally viable but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and all parameters are described in the schema, so the baseline is 3. The description adds no parameter-specific meaning beyond the general concept of disc suggestions and gap filling.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('suggests') and resource ('discs') with a clear purpose ('fill missing shot slots or close voids'). It is structurally distinct from siblings like analyze_bag and find_bag_gaps by emphasizing recommendation rather than analysis or detection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies it should be used when the bag has voids or missing shot slots, but it never names alternatives or states when not to use this tool. An agent must infer the selection criteria from the purpose clause alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct primary purpose, but analyze_bag returns both gap and overlap findings, which overlaps with find_bag_gaps and detect_overlap. This could create ambiguity when choosing between broad analysis and targeted diagnostics.
All tool names follow a consistent verb_noun snake_case pattern: analyze, build, detect, find, recommend. The style is uniform and predictable.
Five tools is well-scoped for a specialized disc golf bag analysis server. Each tool covers a meaningful facet of the workflow without unnecessary bloat.
The tool set covers the full analysis lifecycle: overall assessment, gap detection, overlap detection, fill recommendations, and minimal bag construction. No critical workflow dead ends are apparent for the stated domain.