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Mojibake text repair

tradepilot_service_text_mojibake_repair
Destructive

Repair text corrupted by the classic UTF-8-bytes-read-as-Latin-1 mistake (curly quotes, em dashes, common emoji, stray BOM appearing as garbled multi-character sequences). Pattern-matches known corruption sequences; this is a heuristic repair, not full charset detection, and leaves correctly-encoded text unchanged. Price: 0.01 USD. Payment requires explicit wallet authorization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYes
result_expiresNo
idempotency_keyNo
result_signatureNo
payment_signatureNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations indicate destructiveHint=true and idempotentHint=false, but the description adds crucial context: it is heuristic (may not catch all corruption), it leaves correct text unchanged (non-destructive in practice), and it costs 0.01 USD requiring explicit wallet authorization. It also implies payment-related side effects, which is beyond annotations. 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.

Conciseness4/5

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

The description is compact, front-loads the core purpose and constraints, and includes pricing/payment info without excess. It could be slightly clearer about parameter semantics, but no sentence is wasted.

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

Completeness3/5

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

The tool is relatively simple (input text), but the payment flow is a critical operational detail that is only mentioned cursorily. Without output schema or parameter clarification, an agent may not know whether payment_signature is required or how to obtain it. The description is adequate for basic usage but leaves payment mechanics and parameter roles under-specified.

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 description coverage is 0%, so the description must clarify parameters. It explicitly names 'input' as the text to repair, but does not explain the purpose of result_expires, idempotency_key, result_signature, or payment_signature. The description does not elaborate on payment_signature's role beyond linking to wallet authorization, leaving the agent to guess their meaning. This is a gap for a 5-param tool.

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 clearly states the tool repairs text corrupted by a specific encoding mistake, and gives concrete examples of what it handles (curly quotes, em dashes, emoji, BOM). It distinguishes itself from the many writing/analysis siblings by focusing on a technical text-repair task, and the heuristic limitation is clearly stated.

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?

The description explicitly notes when to use (when text shows mojibake patterns) and what it does not do (full charset detection) and that it leaves correctlyencoded text unchanged. It does not name specific sibling alternatives, but the niche is narrow enough that an agent can infer it from the description.

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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