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Glama

Find text through a long or virtual list

tab_find
Destructive

Find visible text on the current page or scroll container by scrolling in bounded steps and returning a fresh snapshot with actionable references when a match is found.

Instructions

Search the current frame for visible text, scrolling a page or one observed vertical scroll container in bounded steps. Use container_ref with its current snapshot_id for a virtual list. Returns a fresh viewport snapshot with actionable refs when found; found:false means no match within the searched range, not proof the whole application lacks it. This changes scroll position but does not click or submit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
frame_idNo
session_idYesSession ID returned by tab_open.
timeout_msNo
max_scrollsNo
snapshot_idNo
container_refNoElement reference from the current snapshot.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

The description discloses side effects (changes scroll position) and non-actions (does not click or submit), which aligns with destructiveHint=true and readOnlyHint=false. It also explains the bounded step search and the fresh snapshot return, adding valuable context beyond 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.

Conciseness5/5

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

Three focused sentences, front-loaded with the core action, followed by specific usage details, then a side-effect note. No redundancy or unnecessary elaboration.

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?

Covers core behavior, return format (fresh snapshot with refs), side effects, and a key interpretation caveat about found:false. Missing explicit detail on timeout_ms/max_scrolls defaults and the exact output structure, but given the annotations and the description, it is reasonably complete for a search tool.

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

Parameters3/5

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

With only 29% schema coverage, the description compensates partially by explaining the container_ref/snapshot_id relationship for virtual lists and implying max_scrolls via 'bounded steps'. However, other parameters like timeout_ms, frame_id, and text receive no additional meaning, leaving gaps for the agent.

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 action (search for visible text) and the resource (current frame), with specific scrolling behavior. It distinguishes itself from sibling tools like tab_extract or tab_verify by focusing on text discovery and returning a snapshot with actionable refs.

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

Usage Guidelines4/5

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

Provides explicit guidance for virtual lists (use container_ref with current snapshot_id) and clarifies the semantics of found:false, which helps the agent interpret results. However, it does not explicitly name alternative tools or state when not to use this tool, so it falls short of a 5.

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