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rsi-ai-platform

rsi-search-pro-mcp

Official

pick_authority_domains

Identify authoritative domains (regulators, agencies, exchanges) for a query before searching. Returns ranked primary and secondary sources with domain-specific instructions and direct landing pages.

Instructions

Decide which AUTHORITY domains a query should be restricted to.

Call this BEFORE any web search when the query has an authoritative
answer — official regulators, statistical agencies, market exchanges,
industry SROs. Returns the ranked list keyed by `primary` and `secondary`.

Args:
    query: The user question (free text).
    indicators: Optional indicator hints (e.g. ["repo_rate", "cpi_inflation"]).
    jurisdiction: ISO code: "IN", "US", "UK", "EU". Drives jurisdiction defaults.
    topic_hint: One of "regulator", "market", "news", "company_ir",
                "statistics", "academic", "any".
    additional_authority_sources: If you've already resolved authority
        sources for the indicators (e.g. ["RBI", "MOSPI"]), pass them
        here — they will be expanded to domains via the AUTHORITY_DOMAINS
        registry and used as the primary set.

Returns:
    {primary, secondary, primary_sources, secondary_sources,
     hints, landing_pages, rationale, query, current_date}

    `hints` (when non-empty) are DOMAIN-SPECIFIC INSTRUCTIONS you MUST
    follow for this query — e.g. "for GST collections, prefer the Excel
    files at gst.gov.in/download/gststatistics over PDF press releases".
    `landing_pages` are URLs you should fetch DIRECTLY (web_fetch_structured)
    before broadening the search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
indicatorsNo
jurisdictionNo
topic_hintNo
additional_authority_sourcesNo
Behavior5/5

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

With no annotations, the description carries full behavioral disclosure. It explains that the tool returns a ranked list with primary/secondary domains, hints (which must be followed), and landing pages (to be fetched directly). This is thorough and goes beyond basic expectations.

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 somewhat long but well-structured with a clear header, usage instruction, parameter list, and return value description. Every sentence adds value, though it could be slightly more concise without losing key information.

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?

Despite no output schema, the description provides a full breakdown of the return type: primary, secondary, sources, hints, landing pages, rationale, etc. The hints and landing pages instructions are particularly valuable. The description is complete for correct usage.

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

Parameters5/5

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

Schema coverage is 0%, but the description includes a detailed Args section explaining each parameter: query (free text), indicators (optional hints), jurisdiction (ISO code), topic_hint (enum values), additional_authority_sources (pre-resolved sources). This adds significant meaning beyond the bare schema.

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 tool's purpose: 'Decide which AUTHORITY domains a query should be restricted to.' It specifies that it is for authoritative queries and lists examples (regulators, statistical agencies). This distinguishes it from sibling tools like web_search and web_search_authoritative.

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 explicitly says 'Call this BEFORE any web search when the query has an authoritative answer' and provides examples of when to use. It does not explicitly state when not to use, but the context is clear. Alternative tools are not named directly, but the purpose implies this is a pre-filter step.

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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