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AIMLPM

AIMLPM/markcrawl

search_pages

Find specific content across previously crawled web pages by searching local archives with keywords. Retrieves ranked results containing page URLs, titles, and contextual text snippets.

Instructions

Search through previously crawled pages by keyword.

Performs case-insensitive keyword search across page titles and text content.
Results are ranked by the number of matching query words found. Each result
includes the page URL, title, and a text snippet showing context around the
first match.

This is a read-only operation on local files — no network requests are made.
Requires a prior crawl_site call to have populated the pages.jsonl file.

Args:
    query: Search query — one or more keywords separated by spaces. All words
        are searched independently (OR logic). Example: "authentication API key".
    jsonl_path: Full path to the pages.jsonl file from a previous crawl. If
        empty, defaults to <WEBCRAWLER_OUTPUT_DIR>/pages.jsonl.
    max_results: Maximum number of results to return. Default: 10. Use lower
        values for focused searches, higher for comprehensive surveys.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
jsonl_pathNo
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, description carries full burden and excels: discloses read-only/local-file nature ('no network requests'), ranking algorithm ('ranked by the number of matching query words'), search logic ('case-insensitive', 'OR logic'), and result structure ('URL, title, and a text snippet').

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?

Well-structured with logical flow from general function to specific behavior to parameters. Length is appropriate given zero schema coverage necessitating detailed Args section. No redundant sentences, though slightly verbose compared to ultra-concise ideal.

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?

Comprehensive for a search tool: covers search mechanics, ranking, result format, safety characteristics, file dependencies, and all three parameters. Output schema exists (per context signals), so brief mention of result contents is sufficient without detailing return structure.

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

Parameters5/5

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

Schema has 0% description coverage (only titles), but description fully compensates: explains query syntax ('one or more keywords separated by spaces', example provided), jsonl_path context ('from a previous crawl', default location), and max_results usage guidance ('lower values for focused searches').

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?

Specific verb+resource ('Search through previously crawled pages by keyword') clearly distinguishes from siblings: contrasts with crawl_site (which populates data) and implies difference from list_pages/read_page by specifying keyword search across content rather than enumeration or retrieval.

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

Usage Guidelines5/5

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

Explicitly states prerequisite dependency: 'Requires a prior crawl_site call to have populated the pages.jsonl file.' This clearly defines when to use (after crawling) and implies when not to use (no crawl data available), providing essential workflow context.

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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