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Glama

Arcgis Peterborough

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

A4.7/5.0
Behavior5/5

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

Discloses behavioral traits beyond annotations: memory is scoped by identifier, authenticated users get persistent memory, anonymous sessions retain for 24 hours, and integration with recall/forget. This adds meaningful context not captured by annotations like idempotentHint or readOnlyHint, with no contradictions.

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?

Three concise sentences with a clear flow: what it does, when to use it, and lifecycle details. No wasted words; every sentence contributes actionable information.

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 no output schema, the description covers purpose, usage, persistence rules, and related tools. It is self-contained and leaves no significant gaps for the agent.

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 input schema has 100% description coverage for both parameters (key and value). The description adds no extra parameter details beyond confirming key-value pair storage, so the schema does the heavy lifting; baseline 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?

The description uses a specific verb 'Save data' and identifies the resource as key-value pairs scoped by identifier, with concrete examples of what to save. It distinguishes from siblings by referencing recall and forget, making the tool's role unambiguous.

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 guidance: 'Use when you discover something worth carrying forward...' and names alternatives with 'Pair with recall to retrieve later, forget to delete.' This clearly tells the agent when to use this tool versus siblings.

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

Multiple tool families overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route questions to the same underlying 5,767 tools with significant functional overlap. Polymarket tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk) also have blurred boundaries around edge detection and fill risk. The ArcGIS tools (search_datasets, layer_info, query_layer) are distinct, but the non-ArcGIS tools dominate and create confusion.

Naming Consistency2/5

The naming conventions are inconsistent across the set. Some tools use verb_noun (ask_pipeworx, query_layer, search_datasets, list_subscriptions), some use bare verbs (forget, recall, subscribe, unsubscribe), and others use descriptive multi-word names (polymarket_fill_risk, scan_competitor_ai_presence, generate_llms_txt). The ask_pipeworx family and polymarket_* family are internally consistent, but the overall set mixes styles without a clear pattern.

Tool Count2/5

34 tools is heavy for a server that appears to be an ArcGIS data server but includes a massive Pipeworx data-research and prediction-market subsystem. The ArcGIS portion only has 3 tools (search_datasets, layer_info, query_layer), while the rest form a separate general-purpose research/betting toolkit. The count feels bloated and unfocused relative to the server's stated name.

Completeness2/5

The ArcGIS surface is incomplete: search_datasets, layer_info, and query_layer offer no update/create/delete or metadata exploration beyond one layer at a time. The Pipeworx portion is broad but lacks clear lifecycle coverage for subscriptions (create/cancel works, but no update), and the memory tools (remember/recall/forget) are peripheral. The set feels like an accidental aggregation of unrelated domains rather than a complete surface for one purpose.

Resources