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n24q02m

WET - Web Extended Toolkit

by n24q02m

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Read-onlyIdempotent

Perform web searches to locate relevant pages, returning titles, URLs, and snippets for quick discovery.

Instructions

Find information across web, academic sources, X/Twitter, or library docs. Returns search result listings (titles, URLs, snippets) -- NOT full page content. To read full content from a URL, use the extract tool instead.

Actions:

  • search: Web search via SearXNG. Example: search(action="search", query="python async patterns")

  • research: Academic/scientific search (Google Scholar, arXiv, PubMed). Example: search(action="research", query="transformer attention mechanism")

  • x: X/Twitter search via xAI. Returns a SYNTHESIZED answer with citations (NOT a link list for extract() -- X blocks direct extraction). Bills ~$0.032/query (grok-4.3). Requires XAI_API_KEY. Example: search(action="x", query="latest reactions to the GPT-5 launch", handles=["OpenAI"], time_range="week")

  • docs: Search library documentation with auto-indexing. Example: search(action="docs", query="how to create routes", library="fastapi")

  • docs_resolve: Free-form library name to ranked library_id list. Example: search(action="docs_resolve", query="react")

  • docs_query: Version-aware library docs query honoring project lock + token cap. Example: search(action="docs_query", library="react", version="latest", topic="useState", query="how to set initial state")

  • docs_lock_project: Detect project manifests (pyproject/package.json/go.mod/Cargo.toml) and lock the library set for Cabinets isolation. Example: search(action="docs_lock_project", project_path="/repo/my-app")

  • similar: Find pages similar to a URL (pass URL as query). Example: search(action="similar", query="https://example.com/article")

Key parameters:

  • query (required for all actions): Search terms or URL (for similar)

  • library (required for docs): Library name, e.g. "react", "fastapi"

  • language: Programming language for disambiguation in docs, e.g. "python", "java"

  • expand: Enable LLM query expansion for broader coverage (default: false)

  • enrich: Fetch actual page content for richer snippets (default: false, adds latency)

  • max_results: Number of results (default: 10)

  • time_range: Recency filter -- day, week, month, year

  • include_domains / exclude_domains: Domain filters

  • handles / exclude_handles (x only): Restrict to / exclude up to 20 X handles (mutually exclusive), e.g. handles=["nasa"]

  • from_date / to_date (x only): ISO8601 date bounds; override time_range for precise windows

  • video (x only): Enable video understanding of linked X media (default: false)

Use help tool with tool_name="search" for full parameter documentation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
topicNo
videoNo
actionYes
enrichNo
expandNo
handlesNo
libraryNo
to_dateNo
versionNo
languageNo
from_dateNo
categoriesNogeneral
time_rangeNo
max_resultsNo
project_pathNo
exclude_domainsNo
exclude_handlesNo
include_domainsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it notes that 'x' returns a synthesized answer with citations (not a link list), mentions billing (~$0.032/query), and explains that 'enrich' adds latency. It also clarifies that results are listings, not full content. Minor gap: no mention of pagination or rate limits, but the description adds substantial context.

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 well-structured with clear sections (Actions, Key parameters) and front-loaded with the core purpose. It is longer than ideal but every sentence adds value—each action has an example, and parameters are grouped logically. The use of bullet-like formatting and examples makes it scannable. Slight deduction for length, but it's justified given the tool's complexity (8 actions, 20 parameters).

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 tool's high complexity (8 actions, 20 parameters, no schema descriptions), the description is remarkably complete. It covers all actions with examples, explains parameter semantics, notes behavioral nuances (e.g., X's synthesized answers, billing), and points to the 'help' tool for full documentation. The output schema exists, so return values are not the description's responsibility. This is a comprehensive description for a complex tool.

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 description coverage is 0%, so the description carries the full burden of explaining parameters. It does this excellently: it lists key parameters with their purpose, defaults, and action-specific applicability (e.g., 'handles / exclude_handles (x only)', 'from_date / to_date (x only)'). It also provides concrete examples for each action, making parameter usage clear. The description fully compensates for the lack of schema descriptions.

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: 'Find information across web, academic sources, X/Twitter, or library docs.' It specifies the verb (find/search), the resource (information across multiple sources), and distinguishes it from the sibling 'extract' tool by explicitly noting it returns listings, not full content. The action list further clarifies each sub-mode.

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?

The description provides explicit when-to-use guidance: it names the alternative 'extract' tool for reading full content, and details each action with examples and specific use cases (e.g., 'research' for academic sources, 'x' for X/Twitter). It also includes exclusions like 'X blocks direct extraction' and notes prerequisites like XAI_API_KEY.

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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