Skip to main content
Glama

Search Talonic Workspace

talonic_search
Read-only

Search your Talonic workspace for documents, fields, sources, or schemas matching a natural-language query. Returns ranked results across all entity types in a single call.

Instructions

STATUS: stable.

Search the user's Talonic workspace for documents, fields, sources, or schemas matching a query. Returns ranked results across all entity types in one call.

USE WHEN:

  • The user wants to find documents but does not know the exact filename or id.

  • The query is conceptual ('contracts mentioning indemnification', 'Acme invoices').

  • You need to narrow a large workspace before calling talonic_extract or talonic_filter.

  • The user asks 'do I have any docs about X' or 'find anything related to X'.

DO NOT USE WHEN:

  • The user has a specific document_id (use talonic_get_document instead).

  • The user wants to apply structured field-value filters like 'amount > 1000' (use talonic_filter).

  • The user wants to extract data from a brand-new document (use talonic_extract).

TIP: The result includes documents, fieldMatches, sources, schemas, and fields. Both fields[] and fieldMatches[] include a filterable boolean. Only entries with filterable: true can be used with talonic_filter. Fields with filterable: false exist in a schema but have no extracted data yet. Pick the entity type the user actually needs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural-language search query, e.g. 'indemnification clauses' or 'Acme invoices Q4'.
limitNoMaximum results per entity type. Default: 5. Increase for broader exploration.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
documentsYesDocuments matching the query.
fieldMatchesYesField-level matches with a filterable flag indicating whether the entry can drive talonic_filter.
sourcesYesSource connections matching the query.
schemasYesSaved schemas matching the query.
fieldsYesField-registry entries matching the query. filterable: true entries are usable with talonic_filter.
Behavior5/5

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

Annotations already provide readOnlyHint and openWorldHint. The description adds valuable behavioral context: 'Returns ranked results across all entity types in one call', result structure details (documents, fieldMatches, sources, etc.), and the note that 'fieldMatches[] include a filterable boolean' and the implication for talonic_filter usage. No contradictions with 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?

The description is well-structured with clear sections (STATUS, purpose, USE WHEN, DO NOT USE WHEN, TIP). It is front-loaded with the purpose. Every sentence adds value, and the length is appropriate for a search tool with multiple alternatives.

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?

Given that the tool has an output schema (context signal true), only 2 parameters, and clear annotations, the description covers all critical aspects: when to use, when not, result structure, and a practical TIP. No gaps in decision-making or behavior understanding.

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 coverage is 100%, so baseline 3. The description does not add new meaning to the 'query' or 'limit' parameters beyond the schema descriptions. The TIP about filterable is about the result, not the parameters. Thus, no extra parameter information is provided.

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 'Search the user's Talonic workspace for documents, fields, sources, or schemas matching a query.' It uses a specific verb 'Search' and resource 'workspace', and lists entity types. The use of 'returns ranked results across all entity types in one call' further clarifies scope. It distinguishes from sibling tools like talonic_get_document and talonic_filter via usage guidelines.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes explicit 'USE WHEN' and 'DO NOT USE WHEN' sections with concrete conditions (e.g., conceptual queries, unknown filename) and directly names alternative tools (talonic_get_document, talonic_filter, talonic_extract). This provides the agent with clear decision criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/talonicdev/talonic-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server