signal-bureau

get_quote

Feed in your requirements — free-form concerns, questions, whole areas of interest — and get back an enumerated quote: your requirements intelligently grouped and disambiguated into well-formed watched topics, each priced flat from the published tariff ($20/topic/month at the opening rate). The count is disclosed in BOTH directions: overlaps are merged, broad requirements are split into the separate daily reports they actually need, and billing.expansion states the requirement-to-topic ratio outright so a split is as visible as a merge. Large baskets are resolved in batches, so a requirement the desk cannot place does not sink the rest: you get a quote for everything it could place, partial: true, and unresolvedRequirements naming what it could not and why — never a topic invented to cover a gap. A quote is not a charge, needs no contact details, and holds for 30 days. Real model work: ~10 quotes/day per network address (shared egress shares the allowance).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`requirements`	Yes	What you want watched, in your own words — one blob of text or bullet points; the desk does the grouping

TDQS

A4.6/5.0

Behavior5/5

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

The description discloses numerous behaviors: merging/splitting logic, partial quotes with unresolvedRequirements, rate limits, no contact details, and holding period. This is especially valuable given no annotations are provided.

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 dense but well-structured, front-loading the core purpose and then adding necessary detail. It's longer than average but every sentence adds critical information for a complex tool.

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?

With no output schema, the description explains key return fields (billing.expansion, partial, unresolvedRequirements) and the behavior under partial resolution. It also covers rate limits and validity period, making it highly complete.

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?

The schema already describes the 'requirements' param well, and the description reinforces it with examples and explains how the requirements are processed (grouped, disambiguated). It adds value beyond the 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 function: feed in requirements and receive an enumerated quote with grouped watched topics and pricing. The verb 'get back' and resource 'quote' are explicit, and the detailed account of grouping/pricing distinguishes it from siblings like ask or create_order.

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?

It explains that this is for requirements that need to be priced and grouped into watched topics, and notes that a quote is not a charge and holds for 30 days. It doesn't explicitly mention alternatives or when not to use, but the context is clear.

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

A4/5.0

Disambiguation5/5

Each tool targets a distinct function: ask is async event queries, get_answer retrieves results, get_signals and top_accelerating provide different signal views, get_entity and search_entities cover entity details and search, etc. No two tools have overlapping purposes, and descriptions clearly separate them.

Naming Consistency4/5

The majority of tools follow a 'get_' prefix for retrieval (13 of 21) and other clear verbs like 'ask', 'create_order', 'propose_topic', 'send_feedback'. A few use noun phrases like 'todays_brief' and 'top_accelerating', which breaks the pattern slightly but are still intuitive. Overall consistent and predictable.

Tool Count5/5

21 tools cover the full scope of the server: exploration, querying, ordering, account management, feedback, and data records. Each tool serves a clear purpose without redundancy, and the count feels well-scoped for the domain.

Completeness4/5

The tool surface covers all major workflows: browsing signals, asking questions, getting detailed reports, ordering, providing feedback, and proposing new topics. Minor gaps exist (e.g., no explicit tool to cancel an order or manage watched topics directly), but core operations are present and agents can handle the domain effectively.

Resources

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