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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. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Adds behavioral details beyond annotations: persistence duration (24 hours for anonymous, persistent for authenticated users), scoping by identifier, and idempotent nature. No contradiction with annotations.

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?

About six sentences, front-loaded with purpose, covering when, how, persistence, and linking to siblings. Almost every sentence adds value; slightly longer than strictly necessary but still efficient.

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 memory tool with full schema coverage and detailed annotations, the description covers purpose, usage, behavior, persistence, and sibling relationships completely.

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 already describes key and value with examples. The description adds minimal new semantics beyond confirming they form a key-value pair.

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' and distinguishes it from siblings by mentioning recall and forget. It provides specific verb and resource.

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 says 'Use when you discover something worth carrying forward' and explains why. It also guides pairing with recall and forget, offering clear context and alternatives.

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

B3.4/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded all performing similar data lookups. Additionally, many tools focus on prediction markets and arbitrage, which are unrelated to the server's implied Go development domain, causing confusion.

Naming Consistency2/5

Tool names follow inconsistent conventions: some use snake_case (e.g., 'latest_version', 'list_versions'), some use underscores in longer names (e.g., 'ai_visibility_check', 'ask_pipeworx_grounded'), and some use colons in descriptions but not in names. This mix reduces predictability.

Tool Count2/5

With 35 tools, the count is high for a server named 'Pkg Go Dev' that only offers a few Go module-related tools (e.g., get_go_mod, list_versions). The majority are unrelated Pipeworx tools, making the scope mismatched and excessive.

Completeness1/5

The tool set severely lacks coverage for Go development tasks. It only includes basic module lookup tools (version listing, mod retrieval) but misses essential operations like dependency analysis, build commands, or testing. The vast majority of tools cover unrelated domains (prediction markets, company profiles, etc.), leaving the server incomplete for its intended purpose.