Analyse disc golf bag lineups across nine core flight roles, spot critical gaps and redundant overlaps, receive gap-filling disc recommendations, and open an interactive Bag Map on app.bagiq.app. Free, public, read-only.
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') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It conveys that this is a non-mutating analysis that returns a set of computed metrics, which is useful, but it does not explicitly state read-only behavior, rate limits, failure conditions, or whether a BagIQ computation has any side effects/costs.
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?
One compact sentence front-loads the action and then lists every meaningful output category; there is no filler, marketing language, or repetition of schema content. All listed items earn their place by telling the agent what result to expect.
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?
For a tool with no output schema and no annotations, the description's return-value list provides necessary output information and the required discs parameter is covered by the schema. However, it lacks guidance on how this comprehensive analysis relates to the specialized sibling tools and does not mention prerequisites or candidate use cases, leaving some selection context incomplete.
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 the schema already documents the discs array and preferred_brand. The description adds no parameter-specific detail beyond implying that the analysis is over the player's bag, so it earns the baseline 3 rather than compensating for any schema gaps.
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 states a specific action ('Performs a complete BagIQ analysis') on a clear resource ('a player's disc golf bag') and enumerates concrete outputs (slot coverage, identity label, gaps, overlaps, flight coordinates). It does not explicitly differentiate itself from specialized siblings like find_bag_gaps or detect_overlap, though the comprehensive output list makes the distinction inferable.
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 phrase 'complete BagIQ analysis' implies this is the whole-bag diagnostic entry point rather than a targeted gap/overlap check, and the return list includes gaps and overlaps. However, there is no explicit statement about when to choose this over build_minimal_bag, detect_overlap, find_bag_gaps, or recommend_bag_fillers, and no exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Extracts an optimal 3-to-5 disc minimalist setup from a larger bag, maximizing shot coverage while detailing necessary compromises.
| Name | Required | Description | Default |
|---|---|---|---|
| discs | Yes | Full disc collection or bag | |
| target_count | No | Target number of discs in the minimal bag (2..6, default 3) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'detailing necessary compromises' which hints at output, but doesn't disclose side effects, return format, or any limitations. For an optimization tool, agents would benefit from knowing whether it only reads the bag or suggests changes.
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, focused sentence that conveys the purpose and value proposition (maximizing shot coverage, detailing compromises). No wasted words, and the core action is front-loaded. Efficient for an agent 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 the complexity of the tool (optimization with a large disc array and a target_count parameter), the description is thin. It doesn't mention the target_count parameter, how the optimization works, or what the output looks like (beyond mentioning compromises). The lack of an output schema and minimal behavioral description leaves gaps an agent may need to infer.
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%, so both parameters are fully described in the schema. The description adds no additional meaning beyond what the schema provides, meeting the baseline of 3. It doesn't enrich parameter understanding, but it's not needed given high coverage.
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 the action (extracts) and resource (minimalist setup from a larger bag) with a specific goal (maximizing shot coverage). It is distinct from sibling tools like analyze_bag or recommend_bag_fillers, though it doesn't explicitly name them. A verb+resource with clear 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?
No explicit guidance on when to use this tool versus siblings. It implies usage for reducing a bag to a minimal set, but doesn't state conditions, exclusions, or alternatives. For a tool with siblings that analyze, detect, and recommend, more direction would help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Detects redundant molds occupying the same flight slot or shot role, ranking pairs by overlap severity and recommending which disc to keep vs cut.
| Name | Required | Description | Default |
|---|---|---|---|
| discs | Yes | List of discs in the bag (minimum 2 discs) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that it ranks pairs and recommends keep/cut decisions, which implies read-only behavior, but it does not explicitly state whether it modifies data, requires specific permissions, or any side effects. The behavioral disclosure is adequate but not exhaustive.
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, well-structured sentence that front-loads the core purpose and adds the ranking/recommendation behavior. Every word earns its place with no fluff.
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 the rich schema and one parameter, the description is fairly complete. It explains the tool's function and outcome (ranking and recommendation), though it does not specify the exact output format. Since there is no output schema, this could be considered a minor gap, but the description still covers the essential context.
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?
The schema covers the single 'discs' parameter with a detailed description of its items and properties (100% coverage). The description adds no parameter-specific meaning beyond implying that the discs are the input, so it does not need to compensate. 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 states a specific verb ('detects') and resource ('redundant molds'), and clearly defines the scope: flight slot or shot role. It also mentions ranking and recommendations, which distinguishes it from siblings like find_bag_gaps or analyze_bag.
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 when to use it (when you want to detect redundant molds and get keep/cut recommendations) but does not explicitly state when not to use it or name alternative tools. The context is clear, but exclusions are absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Identifies missing shot shapes and unserved flight slots across BagIQ's 9 core slot targets (putter, midrange, fairway, and distance drivers), ranking voids by severity.
| Name | Required | Description | Default |
|---|---|---|---|
| discs | Yes | List of discs in the bag |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It usefully discloses that the tool checks against exactly 9 core slot targets and ranks voids by severity, implying a read-only analysis. However, it does not state whether it mutates anything, what the output format is, or any limitations beyond the 9-slot model.
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?
One dense, front-loaded sentence states the action, scope, and ordering behavior with no filler. Every clause adds information an agent needs.
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?
For a one-parameter analysis tool with no output schema, the description provides enough context to understand what will be computed and how results are prioritized. It could mention the exact return shape, but the core behavior and scope are sufficiently specified.
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?
The schema covers 100% of parameter meaning, so the baseline is 3. The description does not add new semantics about the single 'discs' parameter, but none are needed since the schema already documents strings and object forms thoroughly.
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 names a specific verb ('Identifies'), a concrete resource (BagIQ's 9 core slot targets), and a precise outcome (missing shot shapes, unserved flight slots, severity ranking). It is clear enough to stand apart from general bag tools like analyze_bag, though it does not explicitly differentiate itself from siblings.
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 intended case is implied: use this when you need to find gaps across the nine core slots. But there are no explicit conditions, exclusions, or mentions of alternatives such as detect_overlap or recommend_bag_fillers, so an agent must infer when this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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') |
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.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
analyze_bagbuild_minimal_bagdetect_overlapfind_bag_gapsrecommend_bag_fillersClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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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.