oj_fetch_problemFetch one public problem statement from an exact contest/task pair or canonical atcoder.jp task URL. Returns sanitized HTML with preserved math, samples, limits, hashes, and source provenance.
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No arguments | |||
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true. The description adds value by detailing the return format: 'sanitized HTML with preserved math, samples, limits, hashes, and source provenance.' No contradictions.
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 a single sentence that front-loads the purpose and covers key details without extraneous information. Efficient and clear.
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 availability of annotations and output schema, the description adequately covers input methods and output format. It could mention handling of errors or non-existent problems, but overall it is complete for typical use.
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 the schema already fully describes parameters. The description summarizes input options but does not add new semantic detail beyond what the schema provides.
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 action ('Fetch'), the resource ('public problem statement'), and the input format ('exact contest/task pair or canonical atcoder.jp task URL'). It distinguishes from sibling tools like oj_search_problems, which is for searching, not fetching a specific problem.
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 specifies when to use the tool ('from an exact contest/task pair or canonical URL'), implying not to use it for vague identifiers. However, it does not explicitly state when not to use it or mention alternatives like oj_search_problems for incomplete identifiers.
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.