get_caseReturn the full case for a given pair_id (axes 1/2/4) or id (axis 3): malign and benign task prompts, expected decisions, grounding rationale, and bypass patterns. Axis 3 cases are single (unmatched) and use an 'id' field instead of 'pair_id'. Use list_cases to browse available ids.
| Name | Required | Description | Default |
|---|---|---|---|
| axis | Yes | The axis this case belongs to | |
| pair_id | Yes | The pair_id (axes 1/2/4) or id (axis 3) to retrieve |
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?
Annotations already mark readOnlyHint=true, so the description does not need to restate safety. The description adds useful behavioral details: what data is returned (full case with specific fields) and the distinction between axis 3 versus others. No contradictions with annotations.
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 two sentences, front-loaded with the main action, and each sentence contributes essential information (what is returned, axis-specific key, and referral to sibling tool). No wasted words.
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 simplicity, the description covers all necessary aspects: return content, key handling per axis, and a pointer to list_cases for browsing. Combined with schema and annotations, it is fully adequate for correct tool invocation.
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 baseline is 3. The description adds context that for axis 3 the identifier field is 'id' instead of 'pair_id', but the schema only has a 'pair_id' parameter, creating a slight inconsistency. This adds some meaning but also potential confusion.
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 tool 'Returns the full case' and lists specific components (prompts, decisions, rationale, bypass patterns). It distinguishes between axis 3 (using 'id') and axes 1/2/4 (using 'pair_id'), and differentiates from sibling tool list_cases.
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 advises when to use list_cases ('to browse available ids'), implying users should first retrieve valid identifiers. It does not explicitly list exclusion conditions but provides clear context for tool selection.
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 has a distinct purpose: compare_models compares two profiles, get_case retrieves a full case, get_methodology explains the benchmark design, get_results returns calculation profiles, and list_cases lists metadata. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern (compare_models, get_case, get_methodology, get_results, list_cases) using underscores and imperative verbs.
5 tools is well-scoped for a benchmark analysis server. Each tool covers a necessary function without being excessive or lacking.
The tool set covers the full lifecycle of exploring the benchmark: listing cases, retrieving details, understanding methodology, accessing results, and comparing models. No obvious gaps given the read-only purpose.