Skip to main content
Glama

safari_type_text

Type text character-by-character to trigger autocomplete and per-keystroke reactions in search boxes, chat inputs, and other input fields that respond to each key.

Instructions

Type text character-by-character with realistic key events. Best for: search boxes (triggers autocomplete), chat inputs, and fields that react to each keystroke. For rich text editors (Medium, HackerNoon, LinkedIn), use safari_fill instead — it uses framework-native APIs. For code editors (Monaco/CodeMirror), use safari_replace_editor. When using ref, always take a FRESH safari_snapshot first — refs expire after each new snapshot.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoRef ID from safari_snapshot
textYesText to type
receiptNoTab receipt from safari_new_tab — pins this call to that tab (survives reconnects/subagents)
selectorNoCSS selector to focus

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv2.18.1
    • addedInput schema / properties / receipt
      Added value: +{
      +  "description": "Tab receipt from safari_new_tab — pins this call to that tab (survives reconnects/subagents)",
      +  "type": "string"
      +}
  2. Addedv2.11.6
  3. Removedv2.11.3
  4. Addedv2.10.9
  5. Removedv2.10.8
  6. Addedv2.10.5
  7. Removedv2.10.4
  8. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the burden and discloses key behavioral traits: keystroke-by-keystroke input, realistic key events, autocomplete triggering, and ref expiration on new snapshots. It does not clarify whether typing appends to or replaces existing field content, but the disclosed traits are valuable and specific.

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 compact and front-loaded: the core behavior appears first, followed by targeted use cases, alternatives, and a critical ref freshness rule. Every sentence carries actionable information with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter text-input tool with no annotations and no output schema, this is largely complete: use cases, alternatives, and the ref freshness requirement are all covered. The main gap is not distinguishing it from safari_native_type or stating whether it appends to existing text, leaving some ambiguity for very similar siblings.

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 coverage is 100%, so the baseline is 3; the description adds meaningful operational context for the 'ref' parameter by warning that it must come from a fresh safari_snapshot and expires. The selector and receipt parameters are adequately documented in the schema and need no further description.

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 states a specific operation: typing text character-by-character with realistic key events, and identifies target contexts (search boxes, chat inputs). It explicitly distinguishes itself from safari_fill and safari_replace_editor, so an agent can pick the right sibling without opening schemas.

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?

Clear when-to-use guidance is provided via 'Best for' scenarios, and explicit alternatives are named for rich text editors and code editors. It also adds an operational prerequisite for ref usage, making the decision and invocation path unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/achiya-automation/safari-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server