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) |
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. It discloses the tool's behavior: it ranks pairs by overlap severity and recommends which disc to keep or cut. It does not mention any side effects (though it appears read-only), nor does it discuss limitations like handling of locked discs. It covers the core behavior adequately but omits some edge-case handling.
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, dense sentence that conveys the tool's purpose, the ranking behavior, and the recommendation outcome with zero fluff. All information is essential and front-loaded.
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 tool's complexity (nested objects, enums, and a 'locked' flag that should influence recommendations), the description is incomplete. It does not specify the output format (e.g., list of pairs, severity scores, or recommendation structure) since there is no output schema, nor does it mention how locked discs are handled. An agent calling this tool without further context would be uncertain about the response shape.
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' parameter thoroughly, including object structure, enums, and min/max. The description adds no new parameter-level detail beyond implying the input is a list of discs for redundancy analysis. Baseline 3 is appropriate.
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'), a precise resource ('redundant molds occupying the same flight slot or shot role'), and the resulting actions ('ranking pairs by overlap severity and recommending which disc to keep vs cut'). This clearly differentiates it from siblings like find_bag_gaps (gap identification) or recommend_bag_fillers (additions), so an agent can tell them apart without opening schemas.
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 usage for detecting redundancy in a bag and providing cut/keep recommendations. It does not explicitly name alternatives or state when-not-to-use, but the purpose is clear enough that an agent would select it for overlap detection. Missing explicit exclusions, but the context is unambiguous.
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.