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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

A4.4/5.0
Behavior4/5

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

Annotations provide idempotentHint=true, destructiveHint=false, readOnlyHint=false. The description adds valuable behavioral context: 'scoped by your identifier', persistence differences for authenticated vs anonymous users. 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?

Three sentences, each earning its place: first declares purpose, second gives usage guidance with examples, third details scoping and retention. Front-loaded with no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 2 simple parameters, 100% schema coverage, no output schema, and comprehensive annotations, the description adequately covers purpose, usage, and behavioral details. Lacks error handling but sufficient for core understanding.

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?

Input schema covers 100% of parameters with decent descriptions. The description adds illustrative examples for keys (e.g., 'subject_property') and clarifies value as free-text. This enhances understanding beyond the 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 saves data for reuse across conversations or sessions, specifying verb 'save' and resource 'key-value pair'. It distinguishes from siblings recall and forget by mentioning pairing, and provides examples of what to store.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use: 'when you discover something worth carrying forward' with concrete examples. It also mentions pairing with recall and forget, but does not explicitly state when not to use or contrast with other tools beyond those siblings.

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

A3.9/5.0
Disambiguation3/5

Several tool groups (ask_pipeworx/ask_pipeworx_grounded/deep_research, conditions/disease_names, polymarket_* family) have overlapping purposes, requiring careful reading of descriptions to differentiate. While many tools are conceptually distinct, the similarity within domains could lead to agent misselection.

Naming Consistency3/5

Naming is mostly snake_case but patterns vary: verb_noun (ask_pipeworx), noun_noun (entity_profile), single verb (forget, recall), and some adjectives (recent_changes). No consistent structure across the set, though individual names are descriptive.

Tool Count2/5

With 40 tools, the server is overly large for typical coherence. The tool count exceeds the 15–25 range deemed borderline, making it hard for agents to navigate and select efficiently.

Completeness4/5

The surface covers medical coding (ICD, LOINC, UCUM, drugs, procedures), financial data, prediction markets, memory, subscriptions, and meta-tools. Missing but minor elements (e.g., CPT codes) do not significantly hinder common workflows.