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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

A4.9/5.0
Behavior5/5

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

Annotations idempotentHint=true, destructiveHint=false, readOnlyHint=false. Description adds context: scoped by identifier, 24-hour retention for anonymous. No contradictions.

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?

Front-loaded with purpose, then usage, then behavioral details. Every sentence adds value; no waste.

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 key-value store with no output schema, the description provides all necessary information: persistence, scope, pairing with other tools.

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 covers both parameters with descriptions (100% coverage). Description adds useful examples like 'subject_property' and clarifies that value can be any text, slightly exceeding schema.

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 clearly states the tool's purpose: 'Save data the agent will need to reuse later' with specific examples. It distinguishes from siblings like 'recall' and 'forget'.

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?

Explicitly advises when to use: 'when you discover something worth carrying forward'. Pairs with recall and forget, and clarifies scope and persistence differences between authenticated and anonymous users.

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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Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation3/5

While most tools have distinct purposes, there is notable overlap between the ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and deep_research. Similarly, bet_research and polymarket_edges both analyze betting opportunities. These overlapping tools can cause confusion for an agent.

Naming Consistency2/5

Tool names follow a snake_case pattern, but the verbs used are highly varied (ask_, bet_, compare_, deep_, discover_, entity_, fetch_, forget_, generate_, list_, pipeworx_, polymarket_, read_, recall_, recent_, remember_, resolve_, scan_, search_, subscribe_, suggest_, unsubscribe_, validate_). This lack of a consistent verb_noun pattern makes it harder to predict tool names.

Tool Count2/5

34 tools is excessive for an 'Entertainment Feeds' server. The majority of tools are unrelated to entertainment (e.g., SEC filings, FDA drugs, FRED data, Polymarket betting). Many of these should belong to a separate 'data-access' server, making the scope unwieldy and unfocused.

Completeness2/5

For an entertainment feeds server, the set is incomplete. It can list and read curated feeds and fetch arbitrary RSS, but lacks tools for managing subscriptions to those feeds, searching across feeds, or creating feeds. The inclusion of many non-entertainment tools doesn't compensate for these gaps.