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Glama

suggest

Find frequently visited sites from browser history that are not bookmarked, then propose adding them only after user approval.

Instructions

Sites the user opens a lot but never bookmarked (from browser history). Suggest; add only with their OK.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
min_visitsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose one meaningful behavior: additions require user confirmation. That consent requirement is valuable. It still leaves open whether the tool itself is read-only, whether it persists anything, and how history data is scoped or handled.

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

Conciseness3/5

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

It is short and puts the data source first, which is good. But both sentences are telegraphic fragments with dropped subjects and objects, so brevity comes at the cost of clarity rather than from tight editing.

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

Completeness3/5

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

An output schema exists, so return values need not be described, and only two simple parameters exist. Still, for a tool with zero annotations the description leaves gaps: what set of candidates is returned, how the thresholds shape results, and how it differs from the sibling that actually adds entries.

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

Parameters2/5

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

Schema description coverage is 0% with two parameters ('days', 'min_visits'), so the description must compensate and it does not. 'opens a lot' loosely gestures at a visit-count threshold, but neither the time window nor the visit threshold is explained, nor what the defaults (90/30) mean in practice.

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

Purpose3/5

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

The two fragments together convey the resource and criterion: sites frequently opened but never bookmarked, sourced from browser history. However, 'Suggest' has no object and the description never names what it produces (bookmark suggestions), nor does it differentiate from nearby siblings like 'add' or 'search'. The purpose is inferable but not stated cleanly.

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

Usage Guidelines3/5

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

'add only with their OK' implies the intended workflow (this is a preview/consent step, not a direct mutation) and is the closest thing to usage guidance. There is no explicit when-to-use versus alternatives, no mention of prerequisites, and no statement of what the user should do with the result.

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