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restore_file

Restores original values in a redacted file locally using a mapping, without API calls, and reports only the number of placeholders replaced.

Instructions

Put the original values back into a file, locally (no API call). Returns only how many placeholders were restored, not the values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
overwriteNo
input_pathYesFile containing placeholders, e.g. an edited redacted file or an LLM answer saved to disk.
output_pathYesWhere to write the restored file.
mapping_pathYesThe .map.json written by redact_file.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false and openWorldHint=false; the description adds real behavioral value beyond that: the operation is entirely local ('no API call') and the return value is only a restore count, not the restored values. It does not cover overwrite/conflict behavior, but the output disclosure is a genuine addition.

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 short sentences, zero filler, with the local/no-API constraint and the return-value caveat both front-loaded. Every clause earns its place.

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

Completeness5/5

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

For a mutation tool with no output schema, the description supplies the missing return-value semantics (count only) and the execution model (local, no API), which is exactly the information an agent needs that structured fields do not carry.

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 75%, so the schema already explains input_path, output_path, and mapping_path. The description adds nothing about parameter meaning and leaves 'overwrite' to the schema (where it has no description). Baseline 3 is appropriate.

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?

States a specific verb and resource ('Put the original values back into a file') with the inverse-of-redaction semantics clear from context. It does not explicitly name or differentiate itself from redact_file/redact_text, but the operation is unambiguous.

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

Usage Guidelines3/5

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

Usage is implied (restore after a redacted file was edited or an LLM answer saved to disk) but never stated as when-to-use guidance, and no exclusions or prerequisites are given. Adequate but leaves the routing decision to inference.

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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