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Arcgis Puyallup

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

A4.5/5.0
Behavior4/5

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

Beyond annotations (idempotent, non-destructive), the description adds key behavioral details: storage as key-value pairs scoped by identifier, retention policies (persistent for authenticated, 24 hours for anonymous), and the pairing with recall/forget. This significantly enriches the agent's understanding of side effects and state.

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 three sentences, front-loaded with the core action, then usage guidance, and finally behavioral details. Every sentence earns its place, with no redundancy or 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 two-parameter write tool with clear annotations and no output schema, the description is remarkably complete. It covers purpose, usage scenarios, persistence semantics, and related tools, giving the agent all context needed to select and invoke the tool correctly.

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 description coverage is 100% for both parameters, so the schema already fully documents key and value semantics. The description adds context about key-value scoping and examples, but these align with existing schema descriptions rather than adding new parameter-level information. Baseline 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?

The description clearly states the tool's purpose: 'Save data the agent will need to reuse later' with specific examples like 'resolved ticker' and 'user preference'. It distinguishes from siblings by explicitly pairing with 'recall' and 'forget' tools, making it unambiguous which tool to use.

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?

Provides explicit when-to-use guidance: 'Use when you discover something worth carrying forward' and lists concrete scenarios. Also clarifies persistence differences between authenticated and anonymous sessions, which helps the agent decide when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Arcgis Puyallup toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Several tool clusters overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all serve research questions through the same router, and the five polymarket_* tools plus bet_research form a dense prediction-market cluster. Even with detailed descriptions, an agent choosing between these near-synonyms would frequently need extra reasoning or make the wrong pick.

Naming Consistency2/5

Names mix product-prefixed verbs (ask_pipeworx, polymarket_arbitrage), generic verbs (remember, forget, recall, subscribe), and noun phrases (entity_profile, layer_info, recent_alerts). There is no consistent verb_noun or prefix convention across the set, making the tool surface feel patchwork rather than systematically named.

Tool Count2/5

With 34 tools, the count is already on the heavy side, but it is especially mismatched with the server name 'Arcgis Puyallup': only search_datasets, query_layer, and layer_info actually belong to that GIS domain. The rest are a broad Pipeworx research and prediction-market platform, so the set feels bloated and off-scope for the apparent purpose.

Completeness3/5

The ArcGIS read-only surface is minimally reasonable: search, schema inspection, and querying cover basic open-data consumption. The Pipeworx side is quite rich, with memory, subscriptions, lookups, grounded verification, and discovery, but the named GIS domain is thinly served and lacks obvious capabilities like listing all datasets or browsing layers without a keyword. Overall, coverage is uneven and hard to evaluate cleanly because the server mixes two unrelated purposes.

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