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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

A4.7/5.0
Behavior5/5

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

The description adds behavioral context beyond the annotations: storage as a key-value pair scoped by identifier, persistence differences for authenticated vs anonymous sessions, and the ability to pair with recall/forget. It also implies idempotent overwrite behavior consistent with the idempotentHint annotation. No contradiction found.

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?

The description is composed of five short sentences, each earning its place: purpose, usage examples, storage model, persistence, and sibling pairing. It is front-loaded with the core purpose and contains no fluff.

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 full schema coverage and annotations, the description covers all essential context: what to store, when to use it, how storage is scoped, persistence behavior, and related tools. No output schema is needed for a write operation.

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?

The schema already covers 100% of parameters with meaningful descriptions. The tool description adds only the general 'key-value pair' framing without new detail about the parameters themselves. Baseline 3 is appropriate for high schema coverage.

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 opens with a clear verb and resource: 'Save data the agent will need to reuse later.' It also explicitly contrasts with siblings by mentioning 'Pair with recall to retrieve later, forget to delete,' distinguishing the tool from the related retrieve/delete tools.

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 gives concrete when-to-use guidance: 'Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject).' It also references the alternatives (recall, forget) and the session persistence difference, which helps the agent choose correctly.

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

A3.6/5.0
Disambiguation2/5

The tool set mixes general-purpose Pipeworx tools (ask_pipeworx, ai_visibility_check, bet_research) with only three paleontology-specific tools (find_fossils, get_taxon, list_subtaxa). Multiple similar 'ask_pipeworx' variants further blur distinctions, making it difficult for an agent to select the right tool without deep domain knowledge.

Naming Consistency3/5

Tool names are mostly in snake_case and somewhat descriptive, but the naming conventions vary widely: imperative verbs (find_fossils), interrogative (suggest_questions), and nouns (recent_alerts). The presence of multiple 'ask_pipeworx' variants with inconsistent suffixes (beta, grounded) adds confusion.

Tool Count2/5

With 34 tools, the server is oversized for its claimed paleontology focus. The vast majority of tools are unrelated to Paleobiology, making the server feel more like a general-purpose data API than a specialized paleontology tool. A focused server should have a smaller, targeted set.

Completeness2/5

For the Paleobiology Database purpose, the coverage is severely lacking: only three tools are directly relevant (find_fossils, get_taxon, list_subtaxa). Missing essential operations like searching taxa by name, retrieving occurrences by location, or accessing collections data. The tool set is not a coherent interface for the domain.