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Glama

Tools for Agents

by io.github.max124vip-dev

browser_interact

Playwright browser automation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
stepsYes
timeoutNo

Schema Changelog

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

  1. Changed2 schema fields changed
    • removedInput schema / properties / steps / items / properties
      Removed value: -{
-  "action": {
-    "enum": [
-      "click",
-      "fill",
-      "press",
-      "wait",
-      "wait_for",
-      "screenshot",
-      "text"
-    ],
-    "type": "string"
-  },
-  "key": {
-    "type": "string"
-  },
-  "ms": {
-    "type": "integer"
-  },
-  "selector": {
-    "type": "string"
-  },
-  "value": {
-    "type": "string"
-  }
-}
    • removedInput schema / properties / steps / items / required
      Removed value: -[
-  "action"
-]
  2. First observed

TDQS

D1.3/5.0
Behavior1/5

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

With no annotations, the description carries the full burden of explaining side effects, prerequisites, and execution behavior. 'Playwright browser automation' reveals none of this: it doesn't mention that it launches a browser, executes a sequence of steps, may have performance implications, or what happens on failure. This is a significant transparency gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

While the description is concise in word count, it is under-specified rather than appropriately concise. It consists of a single vague phrase that provides no usable information. The calibration examples treat extreme under-specification as a 2, not a 5.

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

Completeness1/5

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

For a tool with 3 parameters (including a complex 'steps' array) and no output schema, this description is grossly incomplete. It fails to describe the input format, execution model, or return value. The tool's behavior is entirely opaque.

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

Parameters1/5

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

Schema description coverage is 0%, and the description adds no meaning beyond the schema. 'steps' is an array of objects, but the description never explains what those objects contain or how they drive the automation. 'timeout' and 'url' are also unexplained. The description fails to compensate for the undocumented parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is a near-tautology: 'Playwright browser automation' restates the tool's name without specifying what 'interact' means (e.g., clicking, filling forms, navigating). It provides no verb or resource details and does not distinguish it from sibling tools like crawl or screenshot.

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

Usage Guidelines1/5

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

No guidance is given on when to use this tool versus alternatives. The description does not mention contexts requiring multi-step browser automation, nor does it exclude simpler alternatives like read_url or screenshot. There is no when-to-use or when-not-to-use advice.

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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TDQS

C2/5.0
Disambiguation1/5

Multiple tools have overlapping or identical purposes, such as ocr_url and ocr_image (both OCR from an image URL), compare_texts and text_diff (both compare or diff texts), extract_url and read_url (both extract webpage content), and content_hash and hash_text (both compute hashes). The boundaries between these tools are unclear, causing a high risk of misselection.

Naming Consistency2/5

Naming conventions are mixed. Many tools use verb_noun (extract_url, validate_email), but others use noun_verb (language_detect, html_clean), single words (advisor, crawl, retrieve), or noun_noun (job_status, page_metadata). This inconsistency makes it harder to predict tool names.

Tool Count1/5

With 100 tools, the server is extremely over-scoped for a generic agent toolkit. While some tools are distinct and useful, the sheer number does not align with a focused purpose; many tools are redundant or highly specialized, and the count exceeds what is typically manageable for an agent to reason about.

Completeness3/5

The toolkit covers a broad range of utilities including extraction, validation, processing, research, memory, and orchestration. However, there are no CRUD tools for creating/updating/deleting resources, no database or file system operations, and no integration beyond web/API basics. This leaves significant gaps for agents that need general lifecycle management, though it does handle many common tasks.

Resources