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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)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already cover the non-read-only, idempotent, non-destructive nature. The description adds valuable context: key-value storage scoped by identifier, and persistence differences between authenticated (persistent) vs anonymous (24-hour) sessions, which is not disclosed by annotations. It does not contradict annotations, though it omits explicit overwrite semantics.

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?

Three sentences, each earning its place: the core action, when to use it, and persistence details alongside sibling references. No filler, no redundancy, and the main purpose is front-loaded.

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 storage tool with no output schema, the description covers the use case, storage semantics, authentication implications, and relationship to recall/forget. It is complete enough for an agent to select and invoke the tool correctly without further context.

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?

The input schema fully describes both parameters with 100% coverage. The description enhances this by explaining the overall purpose ('data the agent will need to reuse later') and the storage model ('key-value pair scoped by your identifier'), giving semantic meaning to how key and value relate. This contextualization goes beyond the schema's simple field definitions.

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 saves data for reuse, using the specific verb 'Save' and a defined resource ('data the agent will need to reuse later'). It distinguishes itself from sibling tools by explicitly pairing with recall for retrieval and forget for deletion, establishing it as the memory-writing tool.

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 says exactly when to use the tool: 'Use when you discover something worth carrying forward' with concrete examples like resolved tickers and preferences, and gives clear alternatives ('Pair with recall to retrieve later, forget to delete'). This provides explicit guidance for choosing among related tools.

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

Several tool groups heavily overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and discover_tools all route to the same 5,798-tool catalog and compete for the same 'answer this question' use case. The Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker) also all detect betting opportunities, making it easy to pick the wrong one.

Naming Consistency2/5

Naming conventions are mixed: verb_noun (ask_pipeworx, compare_entities, validate_claim), noun_noun (entity_profile, polymarket_arbitrage), adjective_noun (recent_changes, deep_research), and get_* for the MHW tools. All names use snake_case, but there is no consistent structural pattern across the set.

Tool Count2/5

35 tools is too many for a coherent server, and the bulk of them (31 tools) are unrelated to the server's apparent 'Mhw' identity, which covers only 4 Monster Hunter World tools. The set reads like three separate servers (MHW game data, Pipeworx research, Polymarket betting) merged into one.

Completeness1/5

For a server named 'Mhw', the MHW surface is severely incomplete: armor, monsters, skills, and weapons exist, but quests, items, decorations, crafting, and locations are missing. The non-MHW tools are broad but belong to a different domain, so the server does not come close to covering its apparent intended purpose.