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Glama

get_stock_activity

Get institutional buying/selling activity trend for a stock over multiple quarters. Shows how many institutions are buying vs selling, net share changes, and value flows — useful for detecting accumulation or distribution patterns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock ticker symbol
quartersNoNumber of quarters to return (default 8 = 2 years)

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool returns historical trend data over quarters, which indicates it is a read-only query. However, it does not mention any behavioral aspects like data source, update frequency, rate limits, or error handling. The description is adequate but not comprehensive.

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 concise with two sentences. The first sentence states purpose and scope, the second lists output content and use case. No filler words, every phrase adds value.

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?

The description adequately explains what the tool does and what it returns, given the complexity of many sibling tools and no output schema. It covers the trend dimension over quarters. It could mention data source or update frequency, but for a data retrieval tool this is sufficient.

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?

Schema coverage is 100%, with both parameters already well-described in the schema (ticker symbol, quarters with default and bounds). The description adds 'over multiple quarters' which is redundant. It does not add new meaning beyond what the schema provides for the parameters.

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 specifies the verb 'Get' and resource 'institutional buying/selling activity trend for a stock over multiple quarters'. It explicitly states the output content (buying vs selling, net share changes, value flows) and distinguishes from siblings like get_institution_holdings by focusing on activity trend rather than snapshot.

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?

The description provides a clear use case: 'useful for detecting accumulation or distribution patterns'. While it implies when to use (for trend analysis), it does not explicitly contrast with alternatives or state when not to use. However, the purpose alone offers sufficient guidance among the sibling tools.

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

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct resource and action, and descriptions explicitly disambiguate similar pairs (e.g., get_congress_member vs get_congress_trades, get_crypto_holder vs get_crypto_holders). No two tools appear to do the same thing.

Naming Consistency4/5

The dominant pattern is get_<noun>, with list_<noun> for enumerations. Minor deviations exist: a bare 'search' tool and the 'sec_' prefix on SEC filing tools break the uniform verb_noun style, but the pattern remains predictable.

Tool Count4/5

At 24 tools, this is on the heavier side, but the server spans multiple financial data domains (SEC filings, stocks, insider trading, crypto, rates, economics), so each tool has a clear purpose. It is just below the 'too many' threshold.

Completeness5/5

The tool surface is remarkably complete for financial data retrieval: SEC filing lifecycle is covered (list -> index -> document), institutional ownership is available from both stock and institution perspectives, and insider/congress/crypto/economic data are all present. No obvious gaps or dead ends.