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by io.github.Kabrawala

Generate public-sector discovery questions

generate_discovery_questions

Use this when prepping a meeting with a federal agency: it returns discovery questions tuned to public-sector selling (fiscal-year timing, contract vehicles, FedRAMP/ATO, incumbents), grounded in the agency's live spending data where possible — each data-backed question cites the number that motivated it with a source URL. Good queries name the agency, what you sell, and the meeting type, e.g. agency="DHS", product_category="zero-trust network security", meeting_context="first_call". Add naics_code to surface expiring-contract questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agencyYesFederal agency the meeting is with — name, acronym, or code, e.g. "DHS".
naics_codeNoOptional NAICS code for your category — adds questions about specific expiring contracts.
meeting_contextNoWhat kind of meeting you are prepping for.first_call
product_categoryYesWhat you sell, in plain words — e.g. "data analytics platform", "zero-trust network security".

TDQS

A4.4/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses that questions are data-backed with URL sources, tuned to public-sector specifics (fiscal-year timing, contract vehicles, FedRAMP/ATO, incumbents). Does not mention auth or rate limits, but is transparent about core behavior.

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?

Two sentences, no wasted words, includes example and context. Front-loaded with key usage guidance, then details. Highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, but description explains return format (discovery questions with data-backed citations). Covers all 4 parameters, usage context, and public-sector nuances. For a tool of this complexity, it is quite complete, though could mention if multiple questions are returned.

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?

Schema description coverage is 100%, so baseline is 3. Description adds value by providing a concrete usage example and explaining the role of naics_code for expiring-contract questions. Explains all four parameters purposefully beyond 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 it generates discovery questions for public-sector selling, with specific verb 'returns discovery questions' and resource. It distinguishes from sibling tools like agency_spend_profile by focusing on question generation rather than data retrieval.

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?

Explicitly states 'Use this when prepping a meeting with a federal agency' and provides an example query. Lacks explicit 'when not to use', but context implies not for non-public sector. Good guidance on optional parameters like naics_code.

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

A4.5/5.0
Disambiguation5/5

Each tool targets a distinct task in the federal sales intelligence domain: spending profiles, expiring contracts, discovery questions, incumbent lookup, and opportunity qualification. There is no ambiguity or overlap between them.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case (e.g., agency_spend_profile, find_expiring_contracts), making them predictable and easy to navigate.

Tool Count5/5

With 5 tools, the server is well-scoped for its purpose of public-sector sales intelligence. Each tool adds clear value without superfluous or missing functionality.

Completeness4/5

The set covers essential workflows: agency spend analysis, contract expiration tracking, discovery question generation, incumbent lookup, and deal qualification. Minor gaps like contract search by keyword or agency list exist but do not hinder the primary use cases.

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