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Glama

Energi Data Dk

by io.github.pipeworx-io

Remember

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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 discloses key behavioral traits beyond annotations: key-value scoping by identifier, persistence duration (authenticated persistent, anonymous 24h), and non-destructive 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?

The description is articulate and front-loaded with the primary action, but every sentence earns its place. Slightly verbose but maintains clarity.

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 no output schema and the simple key-value pattern, the description is complete enough. It explains the storage scope, persistence, and how to pair with sibling tools.

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 has 100% coverage with descriptions for both key and value. The description adds context about the key-value pair and gives concrete examples, providing added value 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's purpose: saving data for reuse across conversations or sessions. It uses a specific verb+resource ('Save data... reuse'), and distinguishes itself from sibling tools like 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?

The description explicitly says when to use (when discovering something worth carrying forward) and pairs with recall for retrieval and forget for deletion, providing 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.

All Energi Data Dk toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

Several tools form overlapping clusters that are hard for an agent to distinguish: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim, discover_tools, and suggest_questions all cover factual/research lookups, and the five Polymarket tools also overlap heavily. ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, making misselection essentially guaranteed in that pair. The descriptions are detailed, but the boundaries between many tools remain unclear at the set level.

Naming Consistency4/5

Almost all tool names are snake_case and mostly follow readable verb_noun or domain-specific patterns, such as ask_pipeworx*, resolve_entity, validate_claim, and polymarket_*. Minor deviations exist — bare verbs like remember/recall/forget/subscribe and noun-style names like spot_prices/co2_intensity — but there is no mixed casing and the overall pattern is predictable.

Tool Count2/5

34 tools is already over the 25+ threshold for a well-scoped server, and the mismatch is much worse because only three tools (co2_intensity, spot_prices, query_dataset) relate to the advertised Energi Data DK domain. The other 31 tools appear to belong to an unrelated general-purpose Pipeworx platform, so the count is not appropriate for the server's stated purpose.

Completeness3/5

For the stated Energi Data DK domain, energy data access is partially covered: two dedicated tools plus query_dataset as a generic escape hatch for all ~100 datasets prevents hard dead ends, but there are no typed tools for most of those datasets and no energy-specific monitoring/alerting. If the real intended domain is the broader Pipeworx platform, coverage is much stronger, but then the server name is misleading.

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