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Search Savvly Q&A Content Library

search_savvly_content
Read-onlyIdempotent

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

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. Use EXACTLY one of: 'employee', 'advisor', 'broker', 'employer', 'universal', or 'general' ('general' is the factual FAQ). Omit to search across all audiences.

Output 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.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • removedOutput schema / properties / filter_applied / properties / audience / anyOf
      Removed value: -[
      -  {
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]
    • addedOutput schema / properties / filter_applied / properties / audience / type
      Added value: +[
      +  "string",
      +  "null"
      +]
    • removedOutput schema / properties / filter_applied / properties / query / anyOf
      Removed value: -[
      -  {
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]
    • addedOutput schema / properties / filter_applied / properties / query / type
      Added value: +[
      +  "string",
      +  "null"
      +]
    • removedOutput schema / properties / filter_applied / properties / section / anyOf
      Removed value: -[
      -  {
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]
    • addedOutput schema / properties / filter_applied / properties / section / type
      Added value: +[
      +  "string",
      +  "null"
      +]
  2. Changed2 schema fields changed
    • removedInput schema / properties / session_id
      Removed value: -{
      -  "description": "REQUIRED on every call after your first. This MCP server associates all of your tool calls for a given task using session_id; a call that arrives without it cannot be associated with your earlier work and is treated as the start of an unrelated task, disconnected from the original goal. Omit it on your first call only — the server will issue one in the _mcp_instructions field of the result (or a trailing [MCP INSTRUCTIONS] text block) — then echo that exact value on every later call. Never invent a value, and do not issue parallel tool calls until the server has issued your session_id. One session_id covers the whole goal from start to finish: when you spawn subagents you MUST give them this same session_id, or their work is severed from yours. Without session_id, this server does not function as intended.",
      -  "type": "string"
      -}
    • removedOutput schema / properties / _mcp_instructions
      Removed value: -{
      -  "description": "Your handles for this task, confirmed by this MCP server on every response, and the instructions for echoing them on later calls. Read and follow.",
      -  "properties": {
      -    "instructions": {
      -      "type": "string"
      -    },
      -    "session_id": {
      -      "description": "Echo this exact value as the session_id argument on every subsequent tool call.",
      -      "type": "string"
      -    }
      -  },
      -  "type": "object"
      -}
  3. Changed17 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / session_id
      Added value: +{
      +  "description": "REQUIRED on every call after your first. This MCP server associates all of your tool calls for a given task using session_id; a call that arrives without it cannot be associated with your earlier work and is treated as the start of an unrelated task, disconnected from the original goal. Omit it on your first call only — the server will issue one in the _mcp_instructions field of the result (or a trailing [MCP INSTRUCTIONS] text block) — then echo that exact value on every later call. Never invent a value, and do not issue parallel tool calls until the server has issued your session_id. One session_id covers the whole goal from start to finish: when you spawn subagents you MUST give them this same session_id, or their work is severed from yours. Without session_id, this server does not function as intended.",
      +  "type": "string"
      +}
    • changedOutput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • addedOutput schema / properties / _mcp_instructions
      Added value: +{
      +  "description": "Your handles for this task, confirmed by this MCP server on every response, and the instructions for echoing them on later calls. Read and follow.",
      +  "properties": {
      +    "instructions": {
      +      "type": "string"
      +    },
      +    "session_id": {
      +      "description": "Echo this exact value as the session_id argument on every subsequent tool call.",
      +      "type": "string"
      +    }
      +  },
      +  "type": "object"
      +}
    • addedOutput schema / properties / filter_applied / properties / audience / anyOf
      Added value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • removedOutput schema / properties / filter_applied / properties / audience / type
      Removed value: -[
      -  "string",
      -  "null"
      -]
    • addedOutput schema / properties / filter_applied / properties / limit / maximum
      Added value: +9007199254740991
    • addedOutput schema / properties / filter_applied / properties / limit / minimum
      Added value: +-9007199254740991
    • addedOutput schema / properties / filter_applied / properties / query / anyOf
      Added value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • removedOutput schema / properties / filter_applied / properties / query / type
      Removed value: -[
      -  "string",
      -  "null"
      -]
    • addedOutput schema / properties / filter_applied / properties / section / anyOf
      Added value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • removedOutput schema / properties / filter_applied / properties / section / type
      Removed value: -[
      -  "string",
      -  "null"
      -]
    • addedOutput schema / properties / matched / maximum
      Added value: +9007199254740991
    • addedOutput schema / properties / matched / minimum
      Added value: +-9007199254740991
    • addedOutput schema / properties / total_in_library / maximum
      Added value: +9007199254740991
    • addedOutput schema / properties / total_in_library / minimum
      Added value: +-9007199254740991
  4. Changed1 schema field changed
    • changedInput schema / properties / audience / description
      Previous value: -"Restrict to one stakeholder audience ('general' is the factual FAQ). Omit to search across all audiences."New value: +"Restrict to one stakeholder audience. Use EXACTLY one of: 'employee', 'advisor', 'broker', 'employer', 'universal', or 'general' ('general' is the factual FAQ). Omit to search across all audiences."
  5. Changed1 schema field changed
    • changedInput schema / properties / audience / description
      Previous value: -"Restrict 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."New value: +"Restrict to one stakeholder audience ('general' is the factual FAQ). Omit to search across all audiences."
  6. Changed1 schema field changed
    • changedInput schema / properties / audience / description
      Previous value: -"Restrict to one stakeholder audience ('general' is the factual FAQ). Omit to search across all audiences."New value: +"Restrict 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."
  7. Changed14 schema fields changed
    • changedInput schema / properties / audience / description
      Previous value: -"Restrict to one stakeholder audience. Omit to search across all audiences."New value: +"Restrict to one stakeholder audience ('general' is the factual FAQ). Omit to search across all audiences."
    • changedInput schema / properties / audience / enum
      Previous value: -[
      -  "employee",
      -  "advisor",
      -  "broker",
      -  "employer",
      -  "universal"
      -]New value: +[
      +  "employee",
      +  "advisor",
      +  "broker",
      +  "employer",
      +  "universal",
      +  "general"
      +]
    • addedInput schema / properties / section
      Added value: +{
      +  "description": "Substring match against section slugs (e.g. 'tax', 'retention', 'eligibility'). Case-insensitive.",
      +  "type": "string"
      +}
    • removedInput schema / properties / subsection
      Removed value: -{
      -  "description": "Substring match against subsection labels (e.g. 'Tax', 'Retention', 'Eligibility'). Case-insensitive.",
      -  "type": "string"
      -}
    • addedOutput schema / properties / available_sections
      Added value: +{
      +  "description": "Section slugs available within the (optionally) selected audience.",
      +  "items": {
      +    "type": "string"
      +  },
      +  "type": "array"
      +}
    • removedOutput schema / properties / available_subsections
      Removed value: -{
      -  "description": "Subsection labels available within the (optionally) selected audience.",
      -  "items": {
      -    "type": "string"
      -  },
      -  "type": "array"
      -}
    • changedOutput schema / properties / entries / items / properties / audience / enum
      Previous value: -[
      -  "employee",
      -  "advisor",
      -  "broker",
      -  "employer",
      -  "universal"
      -]New value: +[
      +  "employee",
      +  "advisor",
      +  "broker",
      +  "employer",
      +  "universal",
      +  "general"
      +]
    • addedOutput schema / properties / entries / items / properties / keywords
      Added value: +{
      +  "items": {
      +    "type": "string"
      +  },
      +  "type": "array"
      +}
    • removedOutput schema / properties / entries / items / properties / subsection
      Removed value: -{
      -  "type": "string"
      -}
    • changedOutput schema / properties / entries / items / required
      Previous value: -[
      -  "id",
      -  "audience",
      -  "section",
      -  "subsection",
      -  "question",
      -  "answer",
      -  "footnotes"
      -]New value: +[
      +  "id",
      +  "audience",
      +  "section",
      +  "question",
      +  "answer",
      +  "footnotes"
      +]
    • addedOutput schema / properties / filter_applied / properties / section
      Added value: +{
      +  "type": [
      +    "string",
      +    "null"
      +  ]
      +}
    • removedOutput schema / properties / filter_applied / properties / subsection
      Removed value: -{
      -  "type": [
      -    "string",
      -    "null"
      -  ]
      -}
    • changedOutput schema / properties / filter_applied / required
      Previous value: -[
      -  "audience",
      -  "subsection",
      -  "query",
      -  "limit"
      -]New value: +[
      +  "audience",
      +  "section",
      +  "query",
      +  "limit"
      +]
    • changedOutput schema / required
      Previous value: -[
      -  "total_in_library",
      -  "matched",
      -  "filter_applied",
      -  "available_subsections",
      -  "entries"
      -]New value: +[
      +  "total_in_library",
      +  "matched",
      +  "filter_applied",
      +  "available_sections",
      +  "entries"
      +]
  8. Changed1 schema field changed
    • changedInput schema / properties / query / description
      Previous value: -"Free-text substring filter applied to questions, answers, and footnotes. Case-insensitive."New value: +"Free-text search over questions, answers, and footnotes (case-insensitive). Multi-word queries match entries containing ANY of the words, ranked by relevance."
  9. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuinely new behavioral context: each entry carries the verbatim answer with disclaimer footnotes, and responses include primary sources such as SEC filings. It doesn't contradict any annotation.

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?

Front-loads what the library is, then when to use it, then what an entry contains. It is somewhat dense with parentheticals (audience list, slug examples), but every sentence carries information and none is filler.

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 an output schema present, return shape needn't be explained, and the description still covers provenance, entry contents, and the presence of source citations. An agent has enough to call it correctly and interpret results.

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

Parameters3/5

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

Schema description coverage is 100%, so all four parameters including the audience enum and section substring matching are fully documented in the schema. The description restates the audience list and gives kebab-case section slug examples, which is helpful color but largely duplicative of structured fields, so baseline 3 applies.

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?

States a specific verb and resource (search the Savvly Q&A Content Library) and describes the corpus composition and its two organizing axes (audience and section). It doesn't explicitly distinguish itself from close siblings like get_savvly_faq, and in fact mentions 'the factual FAQ' as part of this library, which could cause some ambiguity about where FAQ content lives.

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?

Gives a concrete trigger: use it for questions about Savvly's positioning, value props, audience-specific talking points, or Q&A-style messaging. That is clear situational guidance, but there are no explicit exclusions or named alternatives for overlapping needs (e.g. FAQ lookups vs. this library).

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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