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Savvly

savvly-mcp

Search Savvly Q&A Content Library

search_savvly_content
Read-onlyIdempotent

Search audience-tagged questions and answers from Savvly's marketing and FAQ, organized by stakeholder and section. Use it to find positioning, value props, and talking points.

Instructions

Search the Savvly Q&A Content Library — audience-tagged questions and answers compiled from Savvly's marketing collateral plus the factual FAQ, organized by stakeholder (employee, advisor, broker, employer, universal, general) and section (kebab-case slugs, e.g. 'tax-legacy', 'retention-talent-strategy', 'implementation'). Use this when the user asks about Savvly's positioning, value props, audience-specific talking points, or Q&A-style messaging. Each entry carries the verbatim answer plus any disclaimer footnotes attached to it in the source. These facts come from Savvly's own current records; the response includes primary sources (e.g. SEC filings) for reference.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoCap on matched entries returned. Default 20, max 50.
queryNoFree-text search over questions, answers, and footnotes (case-insensitive). Multi-word queries match entries containing ANY of the words, ranked by relevance.
sectionNoSubstring match against section slugs (e.g. 'tax', 'retention', 'eligibility'). Case-insensitive.
audienceNoRestrict to one stakeholder audience ('general' is the factual FAQ). Use the exact lowercase token (the enum is case-sensitive). Omit to search across all audiences.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
entriesYesMatched Q&A entries.
matchedYesCount of entries matching the supplied filters.
filter_appliedYesEcho of the filters that produced this result set.
total_in_libraryYesTotal Q&A entry count in the library across all audiences.
available_sectionsYesSection slugs available within the (optionally) selected audience.
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive. Description adds that entries include verbatim answers, disclaimer footnotes, and primary sources, enhancing transparency beyond annotations.

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?

Four sentences, front-loaded with purpose, followed by content organization, usage guidance, and data provenance. No filler, every sentence serves a clear function.

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 4 parameters (0 required), full schema coverage, and an output schema present, the description covers all aspects: what is searched, how results are organized, when to use, parameter details, and output characteristics.

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 covers 100% of parameters, but description enriches with examples (e.g., section slugs like 'tax-legacy') and clarifies enum usage (case-sensitive, 'general' for FAQ). Adds meaningful context.

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 searches the Savvly Q&A Content Library, specifies it for audience-tagged questions/answers organized by stakeholder and section, and distinguishes from sibling tools like check_savvly_eligibility and get_savvly_faq.

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 instructs use when the user asks about positioning, value props, audience-specific talking points, or Q&A-style messaging. Provides clear context but does not explicitly name alternative tools.

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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