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Get CodeChef solved problems

get_solved_problems
Read-only

Retrieve unique CodeChef problems a user has solved, including each contest source and reported total solved count, with a limit to control result size.

Instructions

Return the unique problem names a user has solved (as listed on their profile), with the contest each came from, plus their reported total solved count. Capped by 'limit' to protect context size.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "handle": "<handle>"
    },
    "name": "get_solved_problems"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of problem names to return (default 200).
handleYesCodeChef username/handle, e.g. 'gennady.korotkevich'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A3.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint and openWorldHint annotations, the description discloses three useful traits: results are de-duplicated ('unique problem names'), sourced from the profile listing, and capped by 'limit' to protect context size. It also signals that the reported total solved count is separate from the returned list, so the two may not match. It omits auth requirements and behavior for invalid or private handles.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two dense sentences with no filler. The return contents are front-loaded and the limit cap is explained last, which is the right order for an agent deciding whether to call the tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the burden of describing return values, and it does so reasonably: problem names, per-problem contest, and a reported total count. It lacks edge-case behavior such as an unknown handle or a private profile, which keeps it from a 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so both parameters are already fully documented in the schema. The description only adds the rationale for 'limit' (protecting context size) and implies that the handle drives a profile lookup. That is a marginal addition over structured data, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource: return the unique problem names a user has solved, each with its contest, plus the reported total solved count. That is clearly distinct from siblings like get_rating_history or get_contests, but the description never names or contrasts those alternatives, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as get_profile or compare_users. The phrase 'as listed on their profile' hints at the data source but does not tell an agent when this tool is the right choice over its siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.