Dayze — Life Context

List Learned Facts

list_learned_facts

Read-only

List the owner’s polaris_learned_facts with filters and pagination (default 25, max 100). Filter by state (current/stale/disputed), provenance, category, unconfirmed_only, older_than_days, or query. Never dumps thousands. ($0.10; API key required)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_learned_facts"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Page size (default 25, max 100).
`query`	No	Match fact_key or fact_value (substring).
`state`	No	Confirmation state filter.
`offset`	No	Rows to skip (default 0).
`category`	No	Learned-fact category filter, e.g. health.
`provenance`	No	How the fact was learned: stated, observed, inferred or imported, e.g. stated.
`older_than_days`	No	Only rows whose learned_at is older than this many days.
`unconfirmed_only`	No	Only rows that are not confirmed current.

Output Schema

Name	Required	Description	Default
`ok`	Yes
`code`	No
`count`	No
`error`	No
`facts`	No
`limit`	No
`offset`	No
`has_more`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 9, 2026

addedInput schema / properties / category / description

Added value: +"Learned-fact category filter, e.g. health."

addedInput schema / properties / provenance / description

Added value: +"How the fact was learned: stated, observed, inferred or imported, e.g. stated."

AddedNov 9, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already declare this a safe, closed-world read, so the bar is lower, and the description still adds real value: the $0.10 cost, the API key requirement, and the 'Never dumps thousands' pagination expectation are behavioral facts not present in the annotations. It does not explain ordering or what happens at offset beyond the result set, keeping it short of a 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?

Three short sentences lead with purpose, then filters, then the pagination caution, with cost and auth appended tersely. The filter enumeration partially duplicates the schema, but nothing is padded or rambling.

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 an 8-parameter read tool with a full output schema, the description covers scope, filtering, pagination limits, cost, and auth. Combined with the output schema handling return values, the only minor gap is result ordering, which is unlikely to block a correct invocation.

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?

With 100% schema coverage, the schema already documents every parameter including the defaults (25/100), enum values (current/stale/disputed), and provenance options. The description mostly restates that filter set without adding syntax, precedence, or combination behavior beyond what the schema provides, so the 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?

The description names a specific verb and resource ('List the owner's polaris_learned_facts') and scopes it to filters and pagination. It is clear which entity is being listed, though it does not explicitly distinguish itself from sibling list tools such as list_clarifications or list_event_fact_corrections.

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?

Usage is implied through the filter menu (state, provenance, unconfirmed_only, older_than_days) and the caution 'Never dumps thousands,' which signals to paginate rather than bulk-retrieve. However, there is no explicit when-to-use versus alternatives guidance, nor any reference to sibling tools like confirm_learned_fact or expire_stale_learned_facts that operate on the same resource.

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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