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Glama

Antevo Wealth

Run technical analysis

run_technical_analysis
Read-onlyIdempotent

Technical analysis for any instrument — signal consensus, regime, or a full backtest.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
benchmarkNo
frequencyNoD
identifierYes
trade_modeNosimple
history_daysNo
initial_cashNo
analysis_modeNoanalysis
force_refreshNo
risk_per_tradeNo
identifier_typeNo
transaction_costNo
selected_indicatorsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds the range of analysis modes but nothing about data limitations, calculation cost, or how output differs by mode. That is moderate added context.

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?

One sentence with no filler; it states the resource and the key variants immediately. This is compact and well-structured.

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

Completeness2/5

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

With 12 parameters and 0% schema coverage, this description is too thin for correct advanced usage. A caller can at best invoke defaults with an identifier; configuring signal consensus vs full backtest, benchmark, risk, or indicators requires undocumented knowledge.

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%, and the description does not explain any of the 12 parameters. The three mode labels loosely hint at analysis_mode values, but frequency, history_days, initial_cash, trade_mode, risk_per_trade, transaction_cost, and selected_indicators are left entirely undefined.

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

Purpose4/5

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

The description names the core resource ('technical analysis') and three output modes ('signal consensus, regime, full backtest'), so an agent can infer this runs analysis rather than retrieving data. It lacks an explicit imperative verb and doesn't name any sibling, but the purpose is clear enough.

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?

It does not state when to prefer this tool or explicitly exclude alternatives. The phrase 'for any instrument' plus the three modes implies it is the choice when technical-analysis outputs are needed, but no comparison to sibling getters is offered.

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

C2.8/5.0
Disambiguation3/5

Most tools are distinct, but several pairs overlap in purpose: get_market_data and list_watchlist both return watchlist prices/signals, and the four 'brief' tools have fuzzy boundaries. Descriptions help, but an agent could easily select the wrong one without deeper context.

Naming Consistency4/5

The dominant verb_noun pattern (get_* for details, list_* for collections) is clear and consistent in style. There are minor deviations like lookup_index_by_brand and run_technical_analysis, and several plural collections use get_, but these remain readable and mostly predictable.

Tool Count2/5

39 tools is well past the 25+ threshold and represents a heavy surface for an agent to navigate. The broad wealth domain explains some of the count, but many granular getters could be consolidated or curated.

Completeness3/5

The set covers the advertised wealth surface well—portfolio, risk, credit, real assets, markets, geopolitics, watchlist, goals, family, and documents—but it is read-only and lacks obvious navigation endpoints like list_portfolios or detail views for goals/alerts. Agents can retrieve most data, but not all lifecycle operations or entity enumerations are present.

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