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Glama

Digitalnz

by io.github.pipeworx-io

Remember

remember
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

A4.3/5.0
Behavior4/5

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

Adds context beyond annotations: 'scoped by your identifier', 'persistent memory for authenticated users', '24-hour retention for anonymous sessions'. Transparent about scoping and persistence.

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?

Two sentences with no fluff. First sentence states core purpose, second provides usage context and sibling references. Well-structured and front-loaded.

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?

Fully sufficient for a simple 2-parameter tool. Annotations cover read/write/destructive hints, and description covers scoping and retention. No output schema needed; nothing missing.

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% (all parameters described). Description adds only examples of keys ('subject_property', 'target_ticker'), which provides marginal extra context. Baseline of 3 is appropriate.

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?

Clearly states 'Save data the agent will need to reuse later' and specifies the action (save) and resource (key-value pairs). Distinguishes from sibling tools '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 Guidelines4/5

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

Provides explicit when to use: 'when you discover something worth carrying forward'. Mentions pairing with recall and forget. Lacks explicit when-not scenarios, but the usage context is well defined.

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

A3.7/5.0
Disambiguation2/5

The tool set contains multiple clusters with heavy overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to the same underlying data sources, making it ambiguous which to choose. Similarly, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and bet_research all target prediction-market opportunities with fuzzy boundaries between them. The three DigitalNZ tools (search, record, search_within) are distinct, but the rest of the set obscures their purpose.

Naming Consistency3/5

Most tools use snake_case with descriptive names, and the polymarket_* cluster is consistent among itself. However, conventions are mixed: some are verb-first (validate_claim, discover_tools, remember), some are noun-first (entity_profile, recent_changes), and ask_pipeworx_beta breaks the pattern with a suffix variant. The naming is readable overall but not uniform.

Tool Count2/5

At 33 tools, the server exceeds the 25-tool threshold for a 'too heavy' count. The vast majority of tools belong to the Pipeworx data-query and prediction-market domains rather than DigitalNZ, which is the server's stated name. A focused DigitalNZ server would need closer to 5-10 tools; a Pipeworx server would still be over-packed at 33 given the functional overlap.

Completeness2/5

For the DigitalNZ domain, the surface is severely incomplete: only search, record, and search_within exist, with no browse, filter, facet, or contribution capabilities. The Pipeworx side is more complete but still has gaps (e.g., no direct per-source query tools, and several tools soft-fail on sunset APIs). The server tries to cover two unrelated domains and satisfies neither fully.

Resources