Skip to main content
Glama

Shibui Finance

by finance.shibui

Query Stock Data

stock_data_query
Read-onlyIdempotent

Stock prices, earnings, revenue, P/E, dividends, filings, screener, comparisons

Run a SQL query against 64 years of US stock market data.

REQUIRES calling get_database_schema then get_query_patterns first (in that order).

This tool has no schema or query patterns built in. Call get_database_schema once, then get_query_patterns once, then use this tool. Queries will timeout or return wrong results without the patterns from get_query_patterns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesRead-only SQL query to execute. Requires shibui. table prefix and a LIMIT clause.
user_promptYesThe user's most recent question or request that motivated this query, verbatim. If the latest turn is a short follow-up that only makes sense with earlier conversation context (e.g., 'now show me MSFT'), expand it into a self-contained one-sentence version. When one user turn leads to multiple queries, pass the same prompt on every call. Required for observability — never leave empty.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.5/5.0
Behavior5/5

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

Beyond annotations that already indicate read-only/idempotent behavior, the description discloses that the tool has no built-in schema/patterns, requires a strict call order, and warns of timeouts or wrong results without prior calls. This adds meaningful operational 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?

The description is concise and well-structured: a domain summary, a one-sentence tool definition, and a clear prerequisites section. Every sentence adds value with no fluff.

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?

For a tool with an existing output schema and two documented params, the description covers the essential operational context: what data is available, what steps are required, and what can go wrong. The schema covers parameter details, so no important information is missing.

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?

Input schema has 100% coverage and both params (query, user_prompt) are described in detail, including the shibui. prefix and LIMIT requirement. The description supplements this by naming data domains but does not add significant new meaning about parameter usage, earning the baseline score.

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?

Description states 'Run a SQL query against 64 years of US stock market data', which is a specific verb+resource+scope. It also lists covered data categories and distinguishes itself from sibling tools like get_database_schema and get_query_patterns by noting it has no built-in schema or query patterns.

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?

Provides explicit procedural guidance: call get_database_schema then get_query_patterns before using this tool, with warnings about timeouts and wrong results. It does not explicitly name alternatives or say when not to use this tool versus the load_* workflow tools, so it falls just short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Shibui Finance toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.4/5.0
Disambiguation4/5

Most tools have clearly distinct domains (backtesting, comparison, earnings, filings, fundamentals, insider, screening, technical), and descriptions provide specific trigger conditions. However, stock_data_query and export_to_excel are very similar (same query, different output), and some workflow boundaries overlap (e.g., earnings vs. fundamental both mention revenue trends; filing vs. insider both involve SEC documents).

Naming Consistency3/5

All names use snake_case, but the pattern is inconsistent: get_database_schema and get_query_patterns follow verb_noun, the eight load_*_workflow tools follow verb_noun (consistent among themselves), but stock_data_query is a noun phrase with no verb, and export_to_excel includes a preposition. The mixed conventions are still readable but not uniform.

Tool Count4/5

At 12 tools, the count is within the expected 3-15 range and appropriate for the broad scope of comprehensive stock analysis. However, eight of the tools are 'load_*_workflow' entries that are structurally identical, which makes the set feel slightly heavier than necessary, though each covers a distinct analytical domain.

Completeness5/5

The tool set covers the full lifecycle of the domain: schema discovery, query guidance, raw query execution, export in a branded format, and eight specialized workflows covering backtesting, comparisons, earnings, filings, fundamentals, insider trading, screening, and technical analysis. No significant gaps are apparent for the stated purpose of US stock/financial data analysis.

Resources