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mcp-polib

by hsiangjenli
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read_po_context

Retrieve a translation entry and its surrounding context from a PO file to see how it fits within the message catalog.

Instructions

Return the target entry plus its surrounding context window.

Responses:

  • 200 (Success): Successful Response

    • Content-Type: application/json

    • Response Properties:

      • target_entry: The requested entry.

      • context_before: Entries preceding the target.

      • context_after: Entries succeeding the target.

    • Example:

{
  "target_entry": "unknown_type",
  "context_before": [
    "unknown_type"
  ],
  "context_after": [
    "unknown_type"
  ]
}

  • 422: Validation Error

    • Content-Type: application/json

    • Response Properties:

    • Example:

{
  "detail": [
    "unknown_type"
  ]
}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
msgidYesThe msgid of the entry to find.
msgctxtNoOptional message context to disambiguate entries with the same msgid.
file_pathYesAbsolute path to the .po file to read.
context_sizeNoNumber of entries before and after to include.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
target_entryNoThe requested entry.
context_afterYesEntries succeeding the target.
context_beforeYesEntries preceding the target.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.9.5

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full transparency burden. It discloses the response shape (target_entry, context_before, context_after), success status, and validation error, which gives an agent a solid picture of behavior. It does not explicitly state that it performs no modifications, but the tool name and 'Return' strongly imply a read-only operation.

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

Conciseness2/5

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

The actual descriptive content is one sentence, but it is followed by a lengthy response-properties section and JSON examples that duplicate what the output schema already provides. Since the output schema exists, this repetition is redundant and reduces conciseness.

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?

The one-line purpose plus fully described schema and output schema gives an agent enough to call the tool correctly. It lacks explicit usage guidance, but the rich structured metadata compensates for most missing context.

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 the input schema fully documents all four parameters, including msgctxt disambiguation and context_size default. The description adds no parameter-level detail beyond this, so baseline 3 is appropriate.

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?

The description opens with a specific verb and resource: 'Return the target entry plus its surrounding context window.' This clearly distinguishes it from sibling tools like read_po and find_fuzzy, which likely handle single reads and fuzzy searches rather than contextual slices.

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?

The phrase 'surrounding context window' implies the tool is for reading an entry with neighboring entries, but there is no explicit statement of when to prefer this over read_po or find_fuzzy. Usage context is inferable, not stated.

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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