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EfrainTorres

ArmaVita Meta Ads MCP

read_web_content

Fetch complete web content records by ID using cache-first retrieval with API fallback for reliable data access in Meta Ads management.

Instructions

Fetch complete record data by ID using cache-first + API fallback behavior.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
resource_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler implementation for the 'read_web_content' tool, which fetches record data by ID using a cache-first approach with an API fallback.
    async def read_web_content(resource_id: str) -> str:
        """Fetch complete record data by ID using cache-first + API fallback behavior."""
        if not resource_id:
            return json.dumps({"error": "resource_id parameter is required"}, indent=2)
    
        meta_access_token: Optional[str] = None
        try:
            meta_access_token = await auth.get_current_access_token()
        except Exception as token_error:
            logger.debug(f"No access token for read_web_content fallback: {token_error}")
    
        try:
            record = await _data_manager.fetch_record(resource_id, meta_access_token)
            if record:
                logger.info(f"Record fetched successfully: {resource_id}")
                return json.dumps(record, indent=2)
    
            return json.dumps({"error": f"Record not found: {resource_id}", "resource_id": resource_id}, indent=2)
        except ValueError as value_error:
            return json.dumps(
                {
                    "error": "invalid_record_id",
                    "details": str(value_error),
                    "supported_prefixes": list(_SUPPORTED_PREFIXES),
                    "resource_id": resource_id,
                },
                indent=2,
            )
        except Exception as e:
            logger.error(f"Error in read_web_content tool: {e}")
            return json.dumps(
                {
                    "error": "Failed to read_web_content record",
                    "details": str(e),
                    "resource_id": resource_id,
  • The registration of the 'read_web_content' tool within the core package.
    "read_web_content",
Behavior3/5

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 adds context about 'cache-first + API fallback behavior', which hints at performance characteristics and error handling, but doesn't cover critical aspects like authentication needs, rate limits, or what happens on failures. It's not misleading, but incomplete for a tool with potential network interactions.

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 a single, efficient sentence that front-loads the core purpose. There's no wasted text, but it could be slightly more structured by separating behavioral details. It's appropriately sized for a simple tool.

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?

Given the tool has 1 parameter with no schema descriptions, no annotations, and an output schema exists (which reduces the need to explain return values), the description is moderately complete. It covers the basic action and a behavioral trait, but lacks details on parameter usage, error cases, or integration with siblings, leaving room for improvement in guiding the agent.

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?

The input schema has 1 parameter with 0% description coverage, so the schema provides no semantic details. The description adds minimal meaning by implying 'resource_id' is used to fetch 'complete record data', but doesn't explain the ID format, scope, or examples. It partially compensates for the low schema coverage but leaves significant gaps.

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

Purpose3/5

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

The description states the tool 'fetch[es] complete record data by ID' which clarifies the verb (fetch) and resource (record data), but it's vague about what 'record data' refers to—web content, ads, or something else—and doesn't distinguish it from sibling tools like 'search_web_content' or 'read_ad'. It's not tautological, but lacks specificity for differentiation.

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

Usage Guidelines2/5

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

The description mentions 'cache-first + API fallback behavior', which implies a performance or reliability context, but provides no explicit guidance on when to use this tool versus alternatives like 'search_web_content' or other 'read_' tools. There's no mention of prerequisites, exclusions, or comparative use cases.

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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