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farena-ai

Sara

by farena-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Remember a fact

remember_fact

Store one fact about the owner in Sara's long-term memory from another app. Sara asks for approval first, then confirms once the fact is saved.

Instructions

Ask Sara to remember one fact about the owner in her long-term memory, marked as told by this app. Use it to store something on purpose (ask_sara is for conversation, and she may or may not keep what is said there); use add_note for longer text. Returns "Remembered (#id): fact" once the owner allows it. Only listed when the owner turns on "Let other apps change things" in Sara, and it always asks first: it returns "Waiting for approval in Sara" and nothing is stored until the owner presses Allow there.

Input Schema

NameRequiredDescriptionDefault
factYesOne short fact about the owner, as a sentence. Up to 400 characters.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.1.1
    • changedInput schema / properties / fact / description
      Previous value: -"One short fact, e.g. \"Prefers tabs over spaces\"."New value: +"One short fact about the owner, as a sentence. Up to 400 characters."
    • addedInput schema / properties / fact / examples
      Added value: +[
+  "Prefers tabs over spaces",
+  "Works from home on Fridays"
+]
    • addedInput schema / properties / fact / maxLength
      Added value: +400
    • addedInput schema / properties / fact / minLength
      Added value: +1
  2. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

With annotations only saying readOnlyHint=false and non-destructive, the description supplies the behavior that matters: it is a two-phase operation that always asks first, returns 'Waiting for approval in Sara' and stores nothing until Allow, and returns 'Remembered (#id): fact' once permitted. That approval gate and attribution behavior cannot be derived from the annotations or schema.

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 with the core action, then alternatives, then return values and preconditions in a logical order with zero filler. It is dense—long compound sentences and quoted literals—but every clause carries information an agent needs to call it correctly.

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?

No output schema exists, and the description compensates by documenting both return strings (approval-pending and success with id). Combined with the availability precondition and the fact that failure to approve means nothing is stored, an agent has everything needed to invoke it and interpret the result.

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% and the 'fact' parameter already documents the 1-400 character sentence constraint with examples. The description only restates 'one fact about the owner' and does not add format or granularity guidance beyond the schema, so the baseline 3 applies.

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?

States a specific verb (remember/store) and resource (one fact about the owner in Sara's long-term memory), plus the 'marked as told by this app' attribution. It explicitly names what it is not (ask_sara is for conversation, add_note is for longer text), so an agent can pick it out of a 17-tool sibling set immediately.

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?

Gives positive guidance ('use it to store something on purpose'), names two alternatives with the exact conditions that select them (ask_sara for conversation, add_note for longer text), and states the availability precondition (owner must enable 'Let other apps change things'). Nothing is left to inference.

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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