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Collected Data

gnosari_collected_data
Read-onlyIdempotent

List, fetch, or summarise data your agents have collected from conversations.

action='list': Browse collected records (leads, feedback, candidates, orders). Filter by agent, template, date range, status, or search text.

action='get': Fetch ONE record's full detail by entity_id, including the per-attribute provenance (which conversation message + verbatim quote each value came from) and a session_excerpt of the surrounding conversation messages. Use this after 'list' to drill into a record.

action='stats': Dashboard totals -- counts by template, status breakdown, trends. Use group_by_agent=True for per-agent breakdown.

Tip: call with action='stats' first to see the big picture, then action='list' to find records, then action='get' for a single record's evidence.

Tip: for a full, filter-aware CSV download of collected data (all matching records, not a single page), use the REST endpoint GET /api/v1/entities/export instead of paging this list action.

Args: action: 'list' to browse records, 'get' for one record's detail, 'stats' for dashboard totals. agent_id: Filter by a specific agent. entity_id: Id of the record to fetch (required for action='get'). template_name: Filter by template name (list only). days: Relative date filter in days. Omit for all-time (no cutoff). status: Filter by data status (list only). search: Search within collected data attributes, agent name, or data type name (list only). skip: Pagination offset (list only). limit: Pagination limit (list only). include_facets: Include filter-aware per-type and per-status facet counts on the response (list only). group_by_agent: Per-agent stats breakdown (stats only).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoRelative date filter in days (e.g. 1=today, 7=last week, 30=last month). Omit for all-time (no date cutoff).
skipNoNumber of records to skip for pagination (list only)
limitNoMaximum records to return (list only, default: 10)
actionNoAction: 'list' to browse records, 'get' to fetch one record's full detail (incl. per-attribute provenance), 'stats' for dashboard totalslist
searchNoSearch within collected data attributes, the agent name, or the data type name (e.g. email, agent name, or 'leads'). List action only.
statusNoFilter by data status. List action only.
agent_idNoFilter by a specific agent to see only its collected data
entity_idNoId of a single collected record to fetch. Required for action='get'.
template_nameNoFilter by template name (e.g. 'candidates', 'leads'). List action only.
group_by_agentNoWhen true with action='stats', returns per-agent breakdown instead of totals
include_facetsNoInclude per-type and per-status facet counts (list action only)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered. The description adds meaningful behavioral context beyond that: it describes what action='get' returns (per-attribute provenance with verbatim quotes and session_excerpt), what 'stats' returns (counts by template, status breakdown, trends), and the pagination model. It doesn't discuss auth or rate limits, which keeps it below 5.

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-loaded one-line purpose followed by per-action breakdowns and two tips. It is somewhat long and the Args section partially restates the schema descriptions, but each section is scannable and earns its place. Minor redundancy with the schema keeps it from a 5.

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?

For an 11-parameter, multi-action tool with an output schema available, the description covers action semantics, workflow, return contents per action, and an alternative bulk path. Nothing an agent needs to select the right action or interpret results is missing.

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 coverage is 100%, so the baseline is 3. The description adds action-conditional semantics the schema does not (agent_id/entity_id roles per action, days meaning 'omit for all-time', and the action-conditional scope of template_name/status/search/skip/limit/include_facets). This exceeds what the structured fields convey.

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 states a specific verb (list/fetch/summarise) and resource (data agents collected from conversations), and breaks the tool into three clearly-scoped actions. It distinguishes itself from siblings like gnosari_collected_data_delete (which is destructive) and gnosari_manage_data_collection (which configures collection).

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?

Explicitly routes between actions ('Use this after list to drill into a record'), gives a recommended workflow (stats -> list -> get), and names an alternative route (REST export endpoint) for bulk downloads when paging is unsuitable. This is unusually complete usage guidance.

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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