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Drillr — The financial MCP for AI agents

by ai.drillr

news_search

Read-only

Use for any news, event, development, or statement question about a company, theme, or the market.

Covers US, Japan, Hong Kong and A-share markets; The ticker filter takes exchange-suffixed symbols: US bare (AAPL), Japan .T (7203.T), Hong Kong .HK (00700.HK), A-share .SH/.SZ (600519.SH).

Returns Markdown: a ## Stories numbered list (each storyline once), then flat ## Events and ## Claims tables (claims = attributed statements: analyst actions, corporate guidance, central-bank remarks). The Events story column refers back to the Stories number. sources counts corroborating reports; first_reported/last_reported give the reporting span. Lowest-ranked stories are dropped to fit length; the meta line flags how many were omitted.

At least one of query/theme/ticker/since/until is required. Per-parameter detail is on the input schema — search_type=claims needs query/ticker/a time window, not theme.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoSemantic query (English). One of query/theme/ticker/since/until required.
sinceNoISO8601; filter time_event >= since.
themeNoTheme word, resolved to the nearest canonical theme. Not valid with search_type=claims.
top_kNoStory count. Default 10, max 50.
untilNoISO8601; filter time_event < until.
tickerNoExact ticker symbol(s) — a single symbol, an array, or a comma-separated string; multiple tickers are an OR/overlap filter. US symbols bare (AAPL); other markets carry their exchange suffix — 7203.T, 00700.HK, 600519.SH. Company names/brands are NOT resolved here; resolve a name via ticker_lookup/company_search first.
order_byNoResult ordering. relevance (default) | event_time (newest event time first) | create_time (most recently ingested first).
search_typeNoall (default) | events | claims (opinions/statements only).

TDQS

A4.3/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint=true), the description details the output format (Markdown with Stories, Events, Claims tables), explains how stories are truncated, and describes columns like sources and time spans. It fully discloses behavioral traits without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a front-loaded purpose, followed by filter details, output explanation, and parameter constraints. It is slightly verbose but every sentence adds useful information; could be more terse without losing clarity.

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?

Given the complexity (8 parameters, no output schema), the description is complete: covers input requirements, market coverage, ticker formats, output structure, and edge cases (e.g., dropped stories). It adequately compensates for the lack of an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage, the baseline is 3, but the description adds extra value by explaining ticker exchange suffixes, OR behavior for multiple tickers, and restrictions on search_type=claims. This goes beyond the schema descriptions.

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 clearly states the tool is for news, events, and statements about companies/themes/markets. It is specific about the resource (news) and the action (search), but does not explicitly differentiate from sibling tools like company_search or ticker_lookup, though the context implies a distinct purpose.

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 clear usage context, including required parameter combinations (e.g., at least one of query/theme/ticker/since/until) and when search_type=claims is invalid with theme. However, it does not explicitly state when not to use this tool or recommend alternatives.

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

A4.6/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: company_search is qualitative discovery, run_sql is quantitative querying, news_search covers news, sec_report_list/search handle filings, ticker_lookup resolves identifiers, and list_tables/get_table_schema/fiscal_utility support exploration. Cross-references between tools (e.g., company_search explicitly defers to run_sql) prevent confusion.

Naming Consistency4/5

Most tools follow a predictable noun_verb or noun_noun pattern (company_search, news_search, ticker_lookup, run_sql, list_tables, get_table_schema). sec_report_list and sec_report_search are clearly related with descriptive suffixes. Minor deviation: fiscal_utility is vaguer than its siblings, but the pattern is otherwise consistent.

Tool Count5/5

9 tools is right-sized for a financial data platform — enough for comprehensive coverage (search, query, schema, news, filings) without redundancy. Each tool serves a distinct purpose and the count fits the domain well.

Completeness5/5

The tool set forms a coherent workflow: ticker_lookup → company_search/run_sql for fundamentals, news_search for events, sec_report_list/search for filings, and list_tables/get_table_schema for schema discovery. The only minor gap is the absence of a direct 'company profiles' tool separate from company_search, but run_sql covers quantitative needs adequately. The surface is complete for a read-only financial analysis MCP.

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