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Awareness — Memory, Knowledge & Agent Markets

awareness_timeline

Bi-temporal fact stream for one entity (active + superseded).

Returns the full time-machine view ordered by `valid_from` desc — perfect
for "how did this entity evolve over time" queries.

Args:
    entity_id: Entity id to scope the timeline to.
    predicate: Optional predicate filter.
    limit: Max facts (1-500).
    offset: Pagination offset.
    memory_id: Target memory id (auto-resolved if omitted).
    api_key: Bearer token for authentication.

Input Schema

NameRequiredDescriptionDefault
limitNo
offsetNo
api_keyNo
entity_idYes
memory_idNo
predicateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does reasonably well: it discloses result ordering (valid_from descending), that superseded facts are included, and that memory_id is auto-resolved when omitted. Auth via api_key is noted. It omits the read-only nature, rate limits, and pagination behavior beyond the offset parameter.

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?

The opening sentence front-loads the core concept, and the Args block is compact with no padding. Some mild redundancy between the second sentence and the first, but nothing that wastes space significantly.

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

Completeness4/5

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

For a read-only tool with no annotations and no output schema, the definition covers what is returned (full bi-temporal view, superseded included) and in what order, plus the scoping and pagination inputs. The shape of individual returned facts is left unspecified, which is a minor gap.

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 0%, so the description must compensate, and it largely does: all six parameters are enumerated, including the limit range (1-500) and the auto-resolution behavior for memory_id, neither of which appears in the schema. The predicate parameter is only described as an 'Optional predicate filter', leaving its accepted format vague.

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 resource and scope: a bi-temporal fact stream for one entity, including both active and superseded facts. This is clearly distinguishable from a plain fact listing. It does not, however, name or contrast against siblings such as awareness_facts or awareness_recall.

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?

Offers one usage cue: it is framed as 'perfect for "how did this entity evolve over time" queries', which implies a historical/audit intent. There is no explicit when-not guidance and no named alternative for simpler fact lookups, so usage is only implied.

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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