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Glama

get_watchlist

Read-only

Get analytical summaries for every ticker on the user's saved watchlist. This supports requests about the user's watchlist, tracked stocks, portfolio tickers, or an overview of tracked assets. Each item includes trend, momentum, volatility, volume, extremes, support/resistance prices, and a notable_changes array of human-readable day-over-day change alerts (e.g. 'entered deep_oversold', 'volume spike', 'trend reversed to downtrend', 'earnings within days', 'squeeze activated', 'MA crossover: golden cross'). Additional per-item fields include squeeze_active, squeeze_days, climax_detected, climax_type, divergence_detected, divergence_type. Plus/Pro plans also return analyst_consensus, earnings_proximity, growth_zone, free_cash_flow. Pro plans also return insider_activity and insider_net_direction. Band fields include _meta stability objects on Plus and Pro plans. Use this only for questions that span the whole tracked set; for a question about one specific ticker use get_summary instead, even if that ticker is on the watchlist. When the question is only whether anything changed, prefer get_watchlist_changes: it returns just the deltas, whereas this returns a full summary per ticker and grows large on a watchlist of many assets. Use add_to_watchlist to save tickers first; an empty watchlist means the user has not saved any tickers yet, not that the lookup failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoThe TickerDB API response payload for this tool call.

Schema Changelog

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

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

Despite annotations already declaring readOnlyHint=true and destructiveHint=false, the description adds substantial behavioral context: it returns a full per-ticker summary that grows large, includes plan-dependent fields, explains empty-watchlist meaning, and discloses the notable_changes format. No contradiction with 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?

The description is long but every sentence adds value: purpose, return field details, plan tiers, alternatives, and edge-case semantics. It is front-loaded with the core purpose and structured logically without redundancy.

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

Completeness5/5

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

Given the complexity of the output (many fields, plan-dependent data, notable_changes), the description is remarkably complete. It covers return value structure, plan variations, watchlist prerequisites, and when to prefer sibling tools, fully compensating for the absence of parameter docs.

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?

The tool has zero parameters, so the baseline is 4. The description appropriately focuses on return semantics and use cases rather than param docs, which are unnecessary here.

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 opens with a specific verb+resource: 'Get analytical summaries for every ticker on the user's saved watchlist.' It clearly distinguishes itself from siblings by naming alternatives (get_summary for single ticker, get_watchlist_changes for deltas) and explicitly states the scope is the whole tracked set.

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?

Explicit usage guidance is provided: 'Use this only for questions that span the whole tracked set; for a question about one specific ticker use get_summary instead' and 'When the question is only whether anything changed, prefer get_watchlist_changes.' It also advises using add_to_watchlist first and clarifies the empty-watchlist semantics, covering exclusions and alternatives.

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

A4.7/5.0
Disambiguation5/5

Each tool targets a distinct resource/action: watchlist mutations, account info, raw candles, schema metadata, filtered searches, per-ticker summaries, and watchlist-wide summaries/deltas. The descriptions explicitly call out when to prefer one tool over another, especially get_watchlist vs get_summary vs get_watchlist_changes.

Naming Consistency5/5

Tool names follow a consistent get_* pattern for retrieval operations, with add_to_watchlist and remove_from_watchlist as clear mutating counterparts. snake_case verb_noun naming is uniform across all 9 tools.

Tool Count5/5

Nine tools is well within the ideal range and each tool earns its place. The set covers data discovery, analytics, raw data access, account management, and watchlist lifecycle without redundant or bloated surface area.

Completeness5/5

The domain of market intelligence and watchlist management is well covered: search/screen, per-ticker summaries, OHLCV data, watchlist add/remove/list, change tracking, schema discovery, and account limits. No obvious dead ends or missing core operations for the stated purpose.