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Answer challenge

answer_challenge
Idempotent

Answer one of a piece's challenges (n starts at 1; see 'capa.retos' in get_piece). The answer is found by looking closely at the piece. A correct answer earns a stamp in your passport. Answer in English or Spanish with a word, a short phrase or a number; case, accents, articles, plurals and units do not matter. Do not list several options.

Input Schema

NameRequiredDescriptionDefault
nYes
answerYes
piece_idYes
visitor_nameYesYour name as a visitor (max 40 chars). The same name always gives the same avatar, stamps and badges. Reading needs no name; writing (guestbook, comments, challenges, the projects board, the hunt) does.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare the safety profile (non-destructive write, idempotent, closed-world), so the description's job is to add context, and it does: a correct answer earns a stamp in the passport. It also discloses matching leniency (case, accents, articles, plurals, units ignored), which is real behavioral information. It does not describe what an incorrect submission returns or whether attempts are limited, leaving the failure path opaque.

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

Conciseness4/5

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

Compact and front-loaded: what it does, where the challenge list is, the payoff, then the answer-format rules. Every sentence carries information, though the paragraph is dense and could be split into a short usage line plus a format line for scannability.

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 still explains the reward outcome (a stamp) and the answer-matching rules, which is enough for an agent to call it correctly. The main residual gap is the incorrect-answer and retry behavior, which matters for a grading tool but is secondary to getting the call right.

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

Parameters4/5

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

Schema coverage is only 25% (only visitor_name is documented), so the description must compensate, and it does for two key parameters: 'n' is defined as a 1-based index into the piece's challenge list, and 'answer' gets precise format rules (English or Spanish, word/short phrase/number, no option lists). Only piece_id is left implicit via its name and additionalProperties restriction.

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

Purpose5/5

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

Names a specific verb and resource ('Answer one of a piece's challenges') and immediately scopes it to a particular numbered challenge with a pointer to where the list lives ('capa.retos' in get_piece). This clearly separates it from siblings like get_piece (read) and submit_hunt/todays_hunt (different reward track).

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

Usage Guidelines4/5

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

Gives the prerequisite path explicitly: read get_piece first, then index into its 'capa.retos' with n starting at 1. It also constrains the answer format and forbids multi-option answers. It does not say what to do if the answer is wrong or whether retries are allowed, which is the only missing usage context.

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

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