list_browsersReturn all browser IDs tracked by caniuse (e.g. chrome, safari, firefox, edge, ios_saf) with their recent version strings; use IDs with the support tool.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Total number of browsers | |
| browsers | Yes | List of browsers with versions |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, idempotent, and non-destructive traits, so the description doesn't need heavy safety disclosure. It adds specific context about the output (all browser IDs and recent version strings) but doesn't discuss pagination or data freshness—acceptable given 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the main purpose, includes practical example IDs, and integrates the usage hint naturally. No redundant wording.
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 parameterless, read-only listing tool with an output schema, the description adequately conveys the scope and output, and it references the downstream tool. It is complete enough for an agent to invoke it correctly.
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 tool has zero parameters, so schema coverage is trivially 100%. The description confirms there is nothing to configure by omitting parameter details. Baseline 4 applies for parameterless tools.
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 returns all browser IDs tracked by caniuse with their recent version strings, using a specific verb ('Return') and resource ('browser IDs'). It further distinguishes itself by referencing the `support` tool, clarifying its role among siblings.
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 instruction 'use IDs with the support tool' provides explicit guidance on when to use this tool (to obtain browser IDs for use with support). It does not spell out exclusions or alternative scenarios, but for a parameterless list tool, the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tool set has significant overlap: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants, and deep_research, entity_profile, compare_entities, recent_changes, and validate_claim all retrieve structured data with overlapping capabilities. The five Polymarket-oriented tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) further blur boundaries. Agents will struggle to select the right tool without reading very long descriptions.
Most tools follow a clear snake_case verb_noun pattern (ask_pipeworx, compare_entities, validate_claim), and the polymarket_* cluster is consistently prefixed. However, a few tools are bare nouns (feature, support, search) and the remember/forget/recall trio deviates from the dominant pattern, creating minor inconsistency.
35 tools is excessive for a server named 'Caniuse' — only 4 tools actually pertain to browser compatibility (feature, support, search, list_browsers), while 31 are Pipeworx data tools. The server name misrepresents the content, and the sheer number overwhelms rather than scopes the surface.
For the caniuse domain, coverage is complete (search, feature, support, list_browsers). The Pipeworx side includes meta-tools (discover_tools, suggest_questions), retrieval, memory, subscriptions, and feedback, but some tools require accounts and there are gaps like no direct way to list all data sources without discover_tools. The overall surface is broad but lacks obvious missing operations for any single coherent domain.