compare_companies
Compare financial metrics across multiple companies side by side
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tickers | Yes | Comma-separated ticker symbols (e.g. AAPL,MSFT,GOOGL) |
Slacking.biz — SEC Financial Data + US Economics + Demographics + FX
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Changed3 schema fields changed
- changed
Input schema / properties / tickers / descriptionPrevious value: -"Array of ticker symbols to compare (e.g. ['AAPL', 'MSFT', 'GOOGL'])"New value: +"Comma-separated ticker symbols (e.g. AAPL,MSFT,GOOGL)" - removed
Input schema / properties / tickers / itemsRemoved value: -{ - "type": "string" -} - changed
Input schema / properties / tickers / typePrevious value: -"array"New value: +"string"
- First observed
TDQS
B3.2/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits like data freshness, latency, output format, or whether it returns standardized metrics. The description is too vague for the agent to understand important execution details.
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 a single clear sentence with no extraneous information, perfectly concise and front-loaded.
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?
No output schema exists, and the description fails to indicate what return values look like (e.g., which metrics, format). The tool's name 'compare_companies' suggests a comparative analysis, but the description omits crucial contextual details about the comparison output.
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 description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond what the schema already provides for the 'tickers' parameter.
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 states the verb 'compare' and the resource 'financial metrics across multiple companies side by side', effectively distinguishing it from sibling tools like batch_query or get_all_financial_data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives such as batch_query, industry_comparison, or screen_companies. The description implies usage for side-by-side comparison but lacks context or exclusions.
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
C2.9/5.0
Disambiguation2/5
Several tool groups have overlapping purposes: fda_drug_labels vs health_drug_search, fda_recalls vs health_recalls, fx_official_rates vs treasury_fx_rates, treasury_debt vs us_debt_current, and get_gdp vs get_bea_gdp. These near-duplicates create real ambiguity for an agent deciding which tool to call.
Naming Consistency2/5
Names mix verb-led styles (get_, search_, compare_, screen_) with domain-led styles (fx_, treasury_, uk_, health_, eurostat_, datausa_). Within the same domain, similar actions use different patterns (get_gdp vs eurostat_gdp vs imf_indicator), making the set feel inconsistent and hard to predict.
Tool Count1/5
75 tools is extreme for any MCP server, especially when many tools are redundant or cover unrelated domains (weather, earthquakes, scholarly search, air quality) outside the stated SEC/economics/demographics/FX focus. This overwhelms agents and burdens context windows.
Completeness3/5
Core domains like SEC financials, major economic indicators, basic demographics, and current FX rates are well covered. However, gaps remain: no historical FX rates, no stock price/quote tool, limited demographic breakdowns, and no ability to fetch full SEC filing text. Some operations end in dead ends.