Performs a complete BagIQ analysis on a player's disc golf bag. Returns slot coverage percentage, bag identity label (e.g. 'Overstable-heavy', 'Chaos bag'), top missing shot gaps, redundant overlaps, and mapped flight coordinates.
| Name | Required | Description | Default |
|---|---|---|---|
| discs | Yes | List of discs currently in the bag (1 to 35 discs) | |
| preferred_brand | No | Optional preferred brand for recommendations (e.g. 'Innova', 'Discraft') |
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 provided, so the description carries the full burden of behavioral disclosure. It describes the outputs but not the operation's side-effect profile (e.g., read-only vs. mutating), any required permissions, or limitations such as handling unknown disc names. For an analysis tool, it likely has no side effects, but that is not stated. The description does not go beyond what a user would expect from the name and schema.
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?
The description is a single, concise sentence that is front-loaded with the core purpose ('complete BagIQ analysis') and then lists the key outputs. There is no filler or redundant information. Every phrase earns its place, making it both efficient and easy to parse.
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?
Given that there is no output schema, the description adequately covers the return values by listing slot coverage, bag identity, gaps, overlaps, and flight coordinates. It does not describe error behavior or how invalid disc entries are handled, but the schema covers input constraints (1-35 discs, disc object structure). For a read-only analysis tool, this is reasonably complete.
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 description coverage is 100%, so both parameters (discs and preferred_brand) are already well documented in the schema. The description does not add any additional semantic detail about parameters, such as how to format the discs array or that preferred_brand is optional. It provides no value beyond the schema, so the baseline 3 applies.
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?
The description clearly states a specific verb+resource: 'Performs a complete BagIQ analysis on a player's disc golf bag.' It enumerates the outputs (slot coverage, identity label, gaps, overlaps, coordinates), making the tool's function obvious. However, it does not explicitly differentiate from sibling tools like find_bag_gaps or detect_overlap, though the 'complete' qualifier hints at broader scope.
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?
There is no guidance on when to use this tool versus its siblings (build_minimal_bag, detect_overlap, find_bag_gaps, recommend_bag_fillers). The description does not mention conditions for choosing this full analysis over more targeted tools, nor does it state exclusions or alternatives. An agent would have to infer usage from the tool's broad output description.
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.
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.
All tool names follow a consistent snake_case verb-first pattern: analyze, build, detect, find, recommend. No mixed conventions or vague naming.
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.
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.