oj_capabilitiesReport the audited anonymous AtCoder read surface and explicitly unsupported operations.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 declare readOnlyHint, idempotentHint, destructiveHint. The description adds context about being 'audited' and 'anonymous', which provides some additional behavioral insight but is not extensive.
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?
Single sentence, perfectly concise, and front-loads the core purpose without any 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 zero parameters, strong annotations, and the presence of an output schema, the description is fully adequate for understanding the tool's function.
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?
No parameters exist, so the description has no burden. Baseline of 4 is appropriate as schema coverage is 100%.
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 reports 'audited anonymous AtCoder read surface and explicitly unsupported operations', using a specific verb and resource. It distinguishes itself from sibling tools (fetch, health, search) by focusing on capabilities.
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 this tool is for discovering supported vs unsupported operations, but does not explicitly state when to use it over alternatives, nor does it provide 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 has a clearly distinct purpose: reporting capabilities, fetching problem statements, checking health, and searching problems. No overlap or ambiguity.
All tools follow the 'oj_' prefix pattern. While one uses a verb-noun format (oj_fetch_problem) and others use nouns (oj_capabilities, oj_health) or noun-verb (oj_search_problems), the overall pattern is recognizable and consistent.
With 4 tools, the server is slightly lean but well-scoped for a read-only interface to AtCoder problems. The tools cover essential operations without unnecessary bloat.
Given the explicit focus on an audited anonymous read surface, the tools provide necessary operations: fetching, searching, health, and capabilities. Missing write operations are intentionally excluded, so the set is reasonably complete for its domain.