resolve_sparks_dimensionCanon record for a single SPARKS dimension by letter (S, P, A, R, K, S2) or name.
| Name | Required | Description | Default |
|---|---|---|---|
| dimension | Yes | Letter (S, P, A, R, K, S2) or name (e.g. Pack-format) |
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 full burden. It mentions 'canon record' but does not define what that contains, nor does it disclose any behavioral traits such as read-only status, authentication needs, or side effects. The agent is left guessing about the output.
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 very concise with one sentence, which is good for front-loading, but it omits important details (like what 'canon record' means) making it borderline under-specified. It earns its place but could be expanded slightly.
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 no output schema and no annotations, the description is insufficient. It does not explain the return format, error conditions, or prerequisites. For a simple tool with one parameter, it is minimally complete but leaves significant gaps for the agent.
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 input schema has 100% description coverage, so baseline is 3. The description adds the context of 'canon record' but does not provide additional semantics beyond what the schema already states (letter or name). It is adequate but not enhanced.
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 verb 'resolve' and the resource 'single SPARKS dimension' via letter or name, distinguishing it from the sibling tool 'list_sparks_dimensions' which would list all. It is specific but could explicitly mention the distinction.
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 is provided on when to use this tool versus siblings like 'list_sparks_dimensions'. The description only states what it does without any context about prerequisites or alternatives.
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 resource (headers, protocols, members, signals, dimensions) with clear actions (get, list, resolve). There is no overlap in functionality; even the two protocol tools differ in granularity (list vs. get).
Naming follows a consistent verb_noun pattern using underscores and lowercase. Minor inconsistency: 'list_sparks_dimensions' uses plural while 'resolve_sparks_dimension' uses singular, but overall the pattern is clear.
With 9 tools covering headers, protocols, members, signals, and dimensions, the count is well-proportioned for the domain. Each tool addresses a specific query type without unnecessary bloat or gaps.
The tool surface provides complete read access to all canonical entities: headers, protocols, members, signals, and dimensions. Listing and resolving operations are covered for each entity, matching the server's stated purpose of querying agent protocol data.