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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
Behavior5/5

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

Description adds behavioral context beyond annotations: scoping by identifier, persistence differences between authenticated and anonymous users (24-hour TTL). 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is concise (4 sentences), front-loaded with purpose, and every sentence adds value. No redundant or vague statements.

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?

For a simple key-value storage tool, description covers scope, persistence, and pairing with recall/forget. Minor omission: no mention of overwrite behavior or confirmation, but idempotentHint covers safety.

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% with parameter descriptions. Description does not add additional semantics beyond what the schema already provides. Baseline score of 3 applies.

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?

Description clearly states 'Save data the agent will need to reuse later' with a specific verb and resource. It distinguishes from sibling tools 'recall' and 'forget' by explaining pairing, and provides examples of use cases.

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?

Description explicitly says 'Use when you discover something worth carrying forward' and gives concrete examples. It does not explicitly state when not to use, but the context is clear.

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
Disambiguation3/5

Most tools have distinct purposes and the descriptions are unusually thorough, but ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and several discovery/prediction-market tools (polymarket_edges vs polymarket_arbitrage, discover_tools vs suggest_questions) occupy overlapping territory. An agent could reasonably route to the wrong variant despite the documentation.

Naming Consistency4/5

The dominant convention is lowercase snake_case with a leading verb (ask_pipeworx, list_subscriptions, validate_claim, resolve_entity), which makes the set predictable. A few noun-first outliers like pipeworx_trending, recent_alerts, and polymarket_edge_tracker are minor deviations rather than a broken pattern.

Tool Count2/5

34 tools is well above the coherence sweet spot for an MCP server, and much of that count is made up of meta-wrappers and convenience variants around the same Pipeworx router. The broad scope explains some of the count, but the surface still feels heavy for a single named server.

Completeness3/5

The Pipeworx side is very complete: lookups, grounded verification, research, entity profiles, comparisons, prediction-market fill checks, subscriptions, and memory all have lifecycle coverage. However, the server is named Obis and only find_occurrences, get_statistics, and get_taxon serve that domain, leaving obvious marine-biodiversity operations like occurrence detail, dataset listing, and download paths missing.