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Lingo.dev MCP Server - World-class i18n implementation with ICU MessageFormat.
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Tool Definition Quality
Score is being calculated. Check back soon.
Available Tools
4 toolsget_framework_docsAInspect
Retrieves authoritative documentation directly from the framework's official repository.
When to Use
Called during i18n_checklist Steps 1-13.
The checklist tool coordinates when you need framework documentation. Each step will tell you if you need to fetch docs and which sections to read.
If you're implementing i18n: Let the checklist guide you. Don't call this independently
Why This Matters
Your training data is a snapshot. Framework APIs evolve. The fetched documentation reflects the current state of the framework the user is actually running. Following official docs ensures you're working with the framework, not against it.
How to Use
Two-Phase Workflow:
Discovery - Call with action="index" to see available sections
Reading - Call with action="read" and section_id to get full content
Parameters:
framework: Use the exact value from get_project_context output
version: Use "latest" unless you need version-specific docs
action: "index" or "read"
section_id: Required for action="read", format "fileIndex:headingIndex" (from index)
Example Flow:
// See what's available
get_framework_docs(framework="nextjs-app-router", action="index")
// Read specific section
get_framework_docs(framework="nextjs-app-router", action="read", section_id="0:2")What You Get
Index: Table of contents with section IDs
Read: Full section with explanations and code examples
Use these patterns directly in your implementation.
| Name | Required | Description | Default |
|---|---|---|---|
| action | No | index | |
| version | No | latest | |
| framework | Yes | ||
| section_id | No | Required if action='read'. Format: 'fileIndex:headingIndex' |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well: it explains the two-phase workflow (discovery/reading), clarifies that docs reflect current framework state (not training data), and describes output formats (index as table of contents, read as full section). It doesn't mention rate limits or authentication needs, but provides substantial behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections (When to Use, Why This Matters, How to Use, What You Get), front-loaded purpose, and zero wasted sentences. The example flow is appropriately placed and concise. Every section earns its place by providing distinct value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 4-parameter tool with no annotations and no output schema, the description is remarkably complete: it covers purpose, usage context, workflow, all parameters, example usage, and output formats. Given the complexity and lack of structured documentation elsewhere, this description provides everything needed for correct tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25%, but the description compensates fully: it explains all 4 parameters with clear semantics, including the two-phase workflow tied to action values, framework parameter source (get_project_context), version default logic, and section_id format requirements. This adds significant value beyond the minimal schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves authoritative documentation from the framework's official repository, specifying the verb 'retrieves' and resource 'documentation'. It distinguishes from sibling tools like get_i18n_library_docs by focusing on framework documentation specifically, not i18n library docs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided: use during i18n_checklist Steps 1-13, don't call independently, and let the checklist coordinate. It clearly states when to use (during checklist steps) and when not to use (independently), with the sibling tool i18n_checklist named as the coordinator.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_i18n_library_docsAInspect
Retrieves authoritative documentation for i18n libraries (currently react-intl).
When to Use
Called during i18n_checklist Steps 7-10.
The checklist tool will tell you when you need i18n library documentation. Typically used when setting up providers, translation APIs, and UI components.
If you're implementing i18n: Let the checklist guide you. It will tell you when to fetch library docs
Why This Matters
Different i18n libraries have different APIs and patterns. Official docs ensure correct API usage, proper initialization, and best practices for the installed version.
How to Use
Two-Phase Workflow:
Discovery - Call with action="index"
Reading - Call with action="read" and section_id
Parameters:
library: Currently only "react-intl" supported
version: Use "latest"
action: "index" or "read"
section_id: Required for action="read"
Example:
get_i18n_library_docs(library="react-intl", action="index")
get_i18n_library_docs(library="react-intl", action="read", section_id="0:3")What You Get
Index: Available documentation sections
Read: Full API references and usage examples
| Name | Required | Description | Default |
|---|---|---|---|
| action | No | index | |
| library | Yes | ||
| version | No | latest | |
| section_id | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively explains the tool's two-phase workflow (discovery and reading), clarifies that it's a read-only operation (implied by 'retrieves'), and provides context on why it matters for correct API usage. However, it lacks details on rate limits, error handling, or authentication needs, which are minor gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (When to Use, Why This Matters, How to Use, What You Get), front-loaded with the core purpose, and every sentence adds value without redundancy. It efficiently conveys necessary information in a readable format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (4 parameters, 0% schema coverage, no output schema, no annotations), the description is mostly complete. It explains the tool's purpose, usage context, parameters, and expected outputs (index and read results). However, without an output schema, it could benefit from more detail on the structure of returned documentation, but the provided information is sufficient for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It adds significant meaning beyond the schema by explaining the purpose of each parameter (e.g., action='index' for discovery, action='read' with section_id for reading), providing default values (version='latest'), and clarifying constraints (library currently only 'react-intl'). This compensates well for the lack of schema descriptions, though it doesn't fully detail section_id format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Retrieves authoritative documentation for i18n libraries (currently react-intl).' It specifies the verb ('retrieves'), resource ('authoritative documentation'), and scope ('i18n libraries'), and distinguishes it from sibling tools like get_framework_docs by focusing on i18n-specific documentation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool: 'Called during i18n_checklist Steps 7-10' and 'The checklist tool will tell you when you need i18n library documentation.' It also mentions alternatives implicitly by referencing the i18n_checklist sibling tool for guidance, ensuring clear context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_project_contextAInspect
Captures the user's project architecture to inform i18n implementation strategy.
When to Use
Called during i18n_checklist Step 1.
The checklist tool will tell you when to call this. If you're implementing i18n:
Call i18n_checklist(step_number=1, done=false) FIRST
The checklist will instruct you to call THIS tool
Then use the results for subsequent steps
Do NOT call this before calling the checklist tool
Why This Matters
Frameworks handle i18n through completely different mechanisms. The same outcome (locale-aware routing) requires different code for Next.js vs TanStack Start vs React Router. Without accurate detection, you'll implement patterns that don't work.
How to Use
Examine the user's project files (package.json, directories, config files)
Identify framework markers and version
Construct a detectionResults object matching the schema
Call this tool with your findings
Store the returned framework identifier for get_framework_docs calls
The schema requires:
framework: Exact variant (nextjs-app-router, nextjs-pages-router, tanstack-start, react-router)
majorVersion: Specific version number (13-16 for Next.js, 1 for TanStack Start, 7 for React Router)
sourceDirectory, hasTypeScript, packageManager
Any detected locale configuration
Any detected i18n library (currently only react-intl supported)
What You Get
Returns the framework identifier needed for documentation fetching. The 'framework' field in the response is the exact string you'll use with get_framework_docs.
| Name | Required | Description | Default |
|---|---|---|---|
| detectionResults | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It effectively describes the tool's behavior: it requires examining project files, identifying framework markers, constructing a detectionResults object, and storing the returned framework identifier. It explains the output's purpose ('for get_framework_docs calls') and the tool's role in a larger workflow. However, it doesn't mention potential errors, rate limits, or authentication needs, which are minor gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (When to Use, Why This Matters, How to Use, What You Get). Each sentence adds value, such as explaining framework differences or workflow steps. It's slightly verbose but efficiently communicates complex information. The front-loaded purpose statement is clear, and the structure aids comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (1 parameter with nested schema, 0% schema coverage, no output schema, no annotations), the description is highly complete. It covers purpose, usage guidelines, parameter semantics, behavioral context, and output usage. It integrates with sibling tools (i18n_checklist, get_framework_docs) and explains the tool's role in the broader i18n implementation process, leaving no significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate fully. It does so by explaining the required detectionResults object in detail: listing all required fields (framework, majorVersion, sourceDirectory, etc.), providing specific values for framework variants and version ranges, and describing what each field represents (e.g., 'Exact variant', 'Specific version number'). This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Captures the user's project architecture to inform i18n implementation strategy.' It specifies the verb ('captures') and resource ('project architecture') with a clear goal ('inform i18n implementation strategy'). It distinguishes from siblings by explaining its role in the i18n workflow versus get_framework_docs, get_i18n_library_docs, and i18n_checklist.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidelines: 'Called during i18n_checklist Step 1' with detailed steps (call checklist first, then this tool). It explicitly states when NOT to use it: 'Do NOT call this before calling the checklist tool.' It also explains the alternative workflow and why the sequencing matters, making it highly actionable for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
i18n_checklistAInspect
⚠️ MANDATORY TOOL FOR ALL I18N WORK ⚠️
THIS IS NOT OPTIONAL. This tool is REQUIRED for any internationalization, localization, or multi-language implementation.
When to Use (MANDATORY)
ALWAYS use this tool when the user says ANY of these phrases:
"set up i18n"
"add internationalization"
"implement localization"
"support multiple languages"
"add translations"
"make my app multilingual"
"add French/Spanish/etc support"
"implement i18n"
"configure internationalization"
"add locale support"
ANY request about supporting multiple languages
Recognition Pattern:
User message contains: [i18n, internationalization, localization, multilingual, translations, locale, multiple languages]
→ YOU MUST call this tool as your FIRST ACTION
→ DO NOT explore the codebase first
→ DO NOT call other tools first
→ DO NOT plan the implementation first
→ IMMEDIATELY call: i18n_checklist(step_number=1, done=false)Why This is Mandatory
Without this tool, you will: ❌ Miss critical integration points (80% failure rate) ❌ Implement steps out of order (causes cascade failures) ❌ Use patterns that don't work for the framework ❌ Create code that compiles but doesn't function ❌ Waste hours debugging preventable issues
This tool is like Anthropic's "think" tool - it forces structured reasoning and prevents catastrophic mistakes.
The Forcing Function
You CANNOT proceed to step N+1 without completing step N. You CANNOT mark a step complete without providing evidence. You CANNOT skip the build check for steps 2-13.
This is by design. The tool prevents you from breaking the implementation.
How It Works
This tool gives you ONE step at a time:
Shows exactly what to implement
Tells you which docs to fetch
Waits for concrete evidence
Validates your build passes
Unlocks the next step only when ready
You don't need to understand all 13 steps upfront. Just follow each step as it's given.
FIRST CALL (Start Here)
When user requests i18n, your IMMEDIATE response must be:
i18n_checklist(step_number=1, done=false)This returns Step 1's requirements. That's all you need to start.
Workflow Pattern
For each of the 13 steps, make TWO calls:
CALL 1 - Get Instructions:
i18n_checklist(step_number=N, done=false)
→ Tool returns: Requirements, which docs to fetch, what to implement[You implement the requirements using other tools]
CALL 2 - Submit Completion:
i18n_checklist(
step_number=N,
done=true,
evidence=[
{
file_path: "src/middleware.ts",
code_snippet: "export function middleware(request) { ... }",
explanation: "Implemented locale resolution from request URL"
},
// ... more evidence for each requirement
],
build_passing=true // required for steps 2-13
)
→ Tool returns: Confirmation + next step's requirementsRepeat until all 13 steps complete.
Parameters
step_number: Integer 1-13 (must proceed sequentially)
done: Boolean - false to view requirements, true to submit completion
evidence: Array of objects (REQUIRED when done=true)
file_path: Where you made the change
code_snippet: The actual code (5-20 lines)
explanation: How it satisfies the requirement
build_passing: Boolean (REQUIRED when done=true for steps 2-13)
Decision Tree
User mentions i18n/internationalization/localization?
│
├─ YES → Call this tool IMMEDIATELY with step_number=1, done=false
│ DO NOT do anything else first
│
└─ NO → Use other tools as appropriate
Currently in middle of i18n implementation?
│
├─ Completed step N, ready for N+1 → Call with step_number=N+1, done=false
├─ Working on step N, just finished → Call with step_number=N, done=true, evidence=[...]
└─ Not sure which step → Call with step_number=1, done=false to restartExample: Correct AI Behavior
User: "I need to add internationalization to my Next.js app"
AI: Let me start by using the i18n implementation checklist.
[calls i18n_checklist(step_number=1, done=false)]
The checklist shows I need to first detect your project context. Let me do that now...Example: Incorrect AI Behavior (DON'T DO THIS)
User: "I need to add internationalization to my Next.js app"
AI: Let me explore your codebase first to understand your setup.
❌ WRONG - should call checklist tool first
AI: I'll create a middleware file for locale detection...
❌ WRONG - should call checklist tool to know what to do
AI: Based on my knowledge, here's how to set up i18n...
❌ WRONG - should use checklist tool to coordinate implementationWhy Sequential Steps Matter
The 13 steps have strict dependencies:
Can't implement routing (step 3) without locale resolution (step 2)
Can't load translations (step 6) without data source (step 5)
Can't use translation API (step 8) without context (step 7)
Can't add UI switcher (step 12) without switching logic (step 11)
Skipping or reordering steps creates broken implementations that are hard to debug.
Common Mistakes to Avoid
❌ "Let me plan out the implementation first" → NO, call the tool ❌ "Let me check your project structure" → NO, call the tool (it will tell you when) ❌ "I'll implement based on my knowledge" → NO, call the tool (it fetches current docs) ❌ "I'll skip step X since it seems optional" → NO, all steps are mandatory ❌ "I've done this before, I know what to do" → NO, frameworks differ, use the tool
The Tool Coordinates Everything
This tool tells you when to:
Call get_project_context (step 1)
Call get_framework_docs (steps 2-13)
Call get_i18n_library_docs (steps 7-10)
Implement specific code (every step)
Run builds (steps 2-13)
Move to the next step (after evidence validation)
Don't try to orchestrate this yourself. Let the tool guide you.
Summary: Your First Action
When user requests i18n support:
Recognize the trigger words (internationalization, localization, i18n, etc)
IMMEDIATELY call: i18n_checklist(step_number=1, done=false)
Follow the instructions it returns
That's it - the tool handles the rest
This is not a suggestion. This is MANDATORY for all i18n work.
| Name | Required | Description | Default |
|---|---|---|---|
| done | Yes | ||
| evidence | No | ||
| step_number | Yes | ||
| build_passing | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure and does so comprehensively. It explains the tool's sequential nature, evidence validation requirements, build check dependencies, and workflow patterns. It details what happens when parameters are provided, how the tool coordinates with other tools, and the consequences of not using it properly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
While well-structured with clear sections and headings, the description is excessively verbose with repetitive emphasis on mandatory usage. Some sections (like 'Why This is Mandatory' and 'Common Mistakes to Avoid') could be condensed without losing essential information. The front-loaded warning is effective, but overall length reduces efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a 13-step workflow tool with no annotations and no output schema, the description provides complete contextual information. It explains the tool's role in coordinating with sibling tools, details the sequential workflow, provides parameter semantics, and includes practical examples. The description fully compensates for the lack of structured metadata.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 4 parameters, the description fully compensates by providing detailed semantic explanations. It clearly explains step_number (1-13, sequential), done (false for instructions, true for submission), evidence (required array structure with file_path, code_snippet, explanation), and build_passing (required for steps 2-13). The description adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's purpose: it's a mandatory checklist tool for internationalization (i18n) work that provides sequential steps, validates evidence, and coordinates implementation. It clearly distinguishes from sibling tools by emphasizing its role as a workflow coordinator rather than a documentation fetcher or context analyzer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides extensive, explicit guidance on when to use this tool versus alternatives. It lists specific trigger phrases, mandates immediate use as the first action for any i18n-related request, and includes a detailed decision tree. It explicitly warns against using other tools first and provides clear examples of correct vs. incorrect AI behavior.
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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