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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

A4.8/5.0
Behavior5/5

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

Annotated as idempotent and non-destructive. Description adds key behavioral details: key-value storage, identifier scoping, 24-hour retention for anonymous, 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?

Single dense paragraph with all necessary information. Could be slightly more structured, but every sentence adds value. No wasted words.

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 write tool with 2 parameters and no output schema, the description fully covers purpose, usage, behavior, persistence, and relationship to siblings. No gaps.

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 already provides descriptions for both parameters (key and value) with 100% coverage. Description adds naming conventions ('subject_property', 'target_ticker') and clarifies value can be any text, providing extra context beyond 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 'Save data the agent will need to reuse later' and provides concrete examples like resolved tickers, addresses, user preferences. It distinguishes from siblings '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 says when to use: 'when you discover something worth carrying forward'. Mentions pairing with 'recall' and 'forget', and notes scoping and persistence differences for authenticated vs anonymous sessions.

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

A3.8/5.0
Disambiguation2/5

Multiple clusters of near-overlapping tools: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are described as sharing identical routing (beta currently matches stable exactly), and polymarket_edges/polymarket_arbitrage/bet_research all surface 'betting opportunities' with only subtle distinctions agents will struggle to select between. ai_visibility_check vs scan_competitor_ai_presence and entity_profile vs compare_entities compound the ambiguity.

Naming Consistency4/5

Names mostly follow a consistent snake_case verb_noun pattern (get_card, list_sets, search_cards, subscribe, unsubscribe, discover_tools, validate_claim). Minor deviations exist (entity_profile, bet_research, remember/recall/forget, pipeline prefix families like ask_pipeworx_* and polymarket_*), but the conventions are readable and predictable overall.

Tool Count2/5

35 tools is heavy per calibration (25+), and the vast majority are unrelated to the server's apparent TCGdex purpose — only 4 of 35 tools touch trading cards. The count is bloated with Pipeworx/Polymarket/memory/subscription tools that belong to a different server.

Completeness2/5

The actual TCGdex subset (list_sets, get_set, search_cards, get_card) covers basic read-only lookup but has gaps — no set search, no type/rarity/attribute filtering, no pagination, no serie endpoints. The other 31 tools serve disparate domains (data lookup, prediction markets, memory, npm scanning), so no coherent domain surface is actually complete.