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Remember

remember
Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already signal nontrivial behavior (readOnlyHint=false, idempotentHint=true, destructiveHint=false), so the bar is lower. The description adds valuable context beyond annotations: storage mechanism ('key-value pair scoped by your identifier') and persistence duration (authenticated vs anonymous sessions). This is meaningful but not exhaustive (e.g., no mention of overwriting behavior beyond idempotency).

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?

Four sentences, each carrying distinct information: purpose, when to use, storage mechanics, and pairings. No redundancy, no filler. The front-loaded verb 'Save' immediately communicates action.

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 a simple two-parameter write tool with no output schema, the description is fully adequate. It covers what the tool does, when to use it, persistence behavior, and how it relates to recall and forget. No critical gaps remain for an agent to invoke it correctly.

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 description coverage is 100%: both parameters (key, value) are already documented with types and examples. The description adds marginal value by framing them as a key-value pair and noting the identifier scoping, but it doesn't meaningfully extend the schema's clarity. Baseline 3 applies because the schema does the heavy lifting.

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 opens with a specific verb and resource: 'Save data the agent will need to reuse later.' It clearly differentiates from siblings by naming recall and forget as complementary tools, and the scope ('across this conversation or across sessions') adds precision.

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?

It explicitly states when to use the tool: 'Use when you discover something worth carrying forward...' and provides alternatives: 'Pair with recall to retrieve later, forget to delete.' This gives the agent clear decision criteria.

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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TDQS

B3.3/5.0
Disambiguation2/5

The tools span vastly different domains (AI visibility, data querying, prediction markets, GIS) with clear descriptions individually, but the set lacks a coherent focus. An agent looking for ArcGIS functionality would be distracted by many unrelated tools, causing confusion in tool selection.

Naming Consistency2/5

Most tool names use snake_case, but there is no consistent verb_noun pattern. Some names are verbs (remember, forget), others are noun phrases (entity_profile, layer_info), and some include underscores inconsistently (generate_llms_txt vs. bet_research). The naming feels arbitrary.

Tool Count1/5

With 33 tools, the count is high, but the vast majority are from Pipeworx and unrelated to the server's stated purpose (Arcgis Roanoke). Only 3-4 tools actually relate to GIS. The tool count is extremely inappropriate for the server's focus.

Completeness1/5

For the implied domain of ArcGIS Roanoke, the tool surface is severely incomplete, lacking CRUD for map layers, spatial queries, or data management. Conversely, the Pipeworx subset is also incomplete on its own (e.g., missing many data sources). The overall surface fails to serve any single domain well.