Trend strength and direction: adx, aroon, chop, psar, vortex, zigzag.
Runs all trend indicators for the ticker, or only the subset named in
`indicators`. `period` sets the history window: "1d","5d","1mo","3mo",
"6mo","1y","2y","5y","10y","ytd","max" (default "2y").
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | 2y | |
| ticker | Yes | ||
| indicators | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses key behaviors: it runs either all trend indicators or a subset named in 'indicators', and the 'period' parameter controls the history window with a clear default. It does not specify output format or error handling, but for a read-only analysis tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: the first sentence states purpose and lists indicators, the second explains mechanics. Every sentence adds value, with no fluff or repetition of schema fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter tool with no output schema, the description covers the essential usage details: which indicators, how to select a subset, and valid period values. It omits explicit return-value information, but the tool's nature as an analysis function makes the output inferable. Slight gap in not stating output shape prevents a 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains the 'indicators' parameter by listing valid indicator names and explains the 'period' parameter by listing all enum values and the default. It adds significant meaning beyond the bare schema, though 'ticker' is self-explanatory.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Trend strength and direction' and lists the specific indicators (adx, aroon, chop, psar, vortex, zigzag). It uses a specific verb ('Runs') and resource ('ticker'), distinguishing it from sibling tools like analyze_momentum and analyze_volatility by focusing on trend indicators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool, implying trend analysis, and shows how to customize via the 'indicators' and 'period' parameters. However, it does not explicitly mention alternatives or exclusions, such as 'for momentum, use analyze_momentum', so it stops short of full when-to-use/not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools overlap significantly: plot_charts is an explicit alias for generate_charts, generate_chart_pack and generate_charts have similar purposes, and backtesting tools like backtest_macd_momentum vs backtest_macd_trend_follower or backtest_mean_reversion_rsi_bb vs backtest_rsi_mean_reversion are easily confused. The sector tools also have fuzzy boundaries.
Most tools follow a clear verb_noun pattern (analyze_*, backtest_*, get_*, generate_*). However, two tools use a 'tool' suffix (analyze_sector_intelligence_tool, find_sector_stock_pipeline_tool) which deviates from the otherwise consistent naming style.
At 25 tools, the server is at the heavy end of the acceptable range. The scope is broad (analysis, backtesting, charting, portfolio optimization, alerts), but redundant chart tools and overlapping backtest strategies inflate the count and hurt focus.
The toolset covers the core domain well: technical analysis, backtesting, trade planning, portfolio optimization, quotes, news, and alerts. Minor gaps exist, such as no watchlist management tool (scanning only) and no direct historical data fetch, but these are workable around the existing tools.