jam_chart
Notable jams from the ElGoose jam charts, optionally filtered to one song.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| song | No | ||
| limit | No |
Notable jams from the ElGoose jam charts, optionally filtered to one song.
| Name | Required | Description | Default |
|---|---|---|---|
| song | No | ||
| limit | No |
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 provided, and the description does not disclose whether the tool is read-only, how 'notable' is defined, or any ordering/sorting behavior. Lacks important behavioral context.
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 extraneous information. Every part is relevant.
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?
With 2 optional parameters, no output schema, and many siblings, the description is too short. It fails to explain what constitutes 'notable', the expected output format, or how the results are ordered.
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 0%, and the description only adds meaning for the 'song' parameter ('optionally filtered to one song') but does not explain the 'limit' parameter or its default value.
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 uses 'Notable jams from the ElGoose jam charts' which clearly indicates the tool retrieves notable jams. It also mentions optional filtering by song, distinguishing it from sibling tools like album_info or song_stats.
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 guidance on when to use this tool versus alternatives like song_history or appearances. The description does not mention context, prerequisites, or exclusion criteria.
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 targets a distinct aspect of the band's data: albums, appearances, setlists, jams, shows, songs, venues, etc. There is no overlap in functionality, making it easy for an agent to select the correct tool.
All tool names follow the snake_case convention (e.g., album_info, get_setlist, song_stats). The naming is descriptive and consistently uses nouns or verb_noun patterns without mixing styles.
With 14 tools, the server is well-scoped for a band discography/event database. Each tool serves a clear purpose and the count is balanced—neither too few nor excessive.
The tool set covers all key operations: searching shows, retrieving setlists, accessing song history and stats, managing albums, venues, jams, appearances, and even health checks. There are no obvious gaps in covering the band's data lifecycle.