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retrieve_entity_snapshot

Retrieve an entity's current or historical state with full provenance, using optional event-time or ingestion-time cutoffs to reconstruct snapshots as of a specific moment.

Instructions

Retrieve the current snapshot of an entity with provenance information. Supports historical snapshots via 'at' parameter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
atNoEvent-time cutoff (ISO 8601). Reconstructs the snapshot from observations whose `observed_at` ≤ this timestamp. Reflects what *happened* by time T, regardless of when the observation was ingested into Neotoma. Use `at_ingested` instead when you need "what did we actually know at time T" semantics.
formatNoResponse text format. `markdown` (default for MCP) returns canonical deterministic markdown for KV-cache stability. `json` returns the raw snapshot payload for programmatic callers.
entity_idNo
at_ingestedNoIngestion-time cutoff (ISO 8601). Reconstructs the snapshot from observations whose `created_at` (row-insertion time) ≤ this timestamp. Excludes backfilled or late-arriving observations that have a past `observed_at` but arrived after this cutoff, preventing look-ahead leaks. When both `at` and `at_ingested` are supplied, both bounds are applied (AND logic): an observation must satisfy `observed_at ≤ at` AND `created_at ≤ at_ingested`.
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions provenance and historical snapshots but omits key behaviors like the default response format (markdown) for KV-cache stability, the existence of the 'at_ingested' parameter for ingestion-time semantics, and any potential side effects. The schema parameter descriptions provide more behavioral context than the tool description itself.

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 two sentences, front-loads the primary purpose, and is entirely free of fluff. It conveys the core function and a key capability without unnecessary detail, making it highly concise and well-structured.

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

Completeness2/5

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

Given the absence of annotations and output schema, the description is too sparse to provide adequate context. It does not explain the response payload, the distinction between 'at' and 'at_ingested', or the optional parameters, leaving a knowledgeable agent to rely solely on the schema. This is incomplete for a tool with four parameters and a rich conceptual model.

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 75%, with detailed descriptions for 'at', 'format', and 'at_ingested'. The tool description adds little beyond mentioning the 'at' parameter, and does not clarify 'entity_id' or 'at_ingested'. Since the schema already provides strong parameter semantics, the description's minimal addition keeps this at baseline.

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?

The description clearly states the tool retrieves an entity snapshot with provenance information, and explicitly mentions historical snapshot support via the 'at' parameter. This distinguishes it from sibling tools like get_relationship_snapshot or retrieve_entities, though it doesn't explicitly differentiate from all related entity retrieval tools.

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

Usage Guidelines3/5

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

The description implies usage for current or historical snapshots but provides no explicit guidance on when to use this tool versus alternatives such as retrieve_entity_by_identifier or retrieve_entities. It does not mention exclusions or when not to use it, leaving usage context implicit.

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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