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All About Ads MCP

read_saved_results

Read-only

Retrieve a paginated subset of saved scraper results by specifying offset, limit, fields, and a substring query to reduce token consumption.

Instructions

Read a paginated slice of items from a previously saved scraper results file.

Results files can be very large. Read in small pages and project only the fields you need to stay within context limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of items to return per call.
queryNoCase-insensitive substring filter. Only items whose JSON contains this string are returned.
fieldsNoIf set, only these top-level keys are included per item. Use to reduce token usage.
offsetNoIndex of the first item to return. Use with limit to paginate.
file_pathYesPath returned by a search tool or list_saved_results. A bare filename also works.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metaYes
itemsYes
offsetYes
returnedYes
total_itemsYes
matched_itemsYes
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds context about large result files and recommends pagination and projection to stay within context limits. No contradictions; it complements the annotations.

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?

The description is concise (three sentences) and front-loaded: the first sentence states the purpose, followed by two sentences of guidance. No wasted words.

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?

Given the complexity (5 parameters, output schema exists), the description covers what the tool does, why it's important (large files), and how to use it (pagination, projection). It is complete for agent selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining why to use parameters like 'limit' and 'fields' ('read in small pages and project only the fields you need'), reinforcing the purpose beyond the schema.

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 clearly states the tool's purpose: 'Read a paginated slice of items from a previously saved scraper results file.' It uses a specific verb ('Read') and resource ('paginated slice of items') and differentiates from siblings like 'list_saved_results' and 'collect_scrape_results' by focusing on pagination and projection.

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 provides clear guidance: 'Read in small pages and project only the fields you need to stay within context limits.' This helps the agent understand when to use pagination and projection. However, it does not explicitly state when not to use this tool or suggest alternatives for cases like retrieving all items at once.

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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