Skip to main content
Glama

Arcgis Allegheny

by io.github.pipeworx-io

Search Within a Source

search_within
Read-onlyIdempotent

Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe document text to search inside (max ~200K chars).
limitNoMax passages to return (1-20, default 5).
queryYesNatural-language query — what passages do you want? E.g. "supply-chain risk", "fiscal year 2024 revenue", "drug interactions with warfarin".

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark read-only, idempotent, non-destructive; description adds substantial context: BGE-base-en embeddings + cosine over 500-char windows, 200K char cap with truncation flagging, and return format (character offsets, similarity scores). No contradiction.

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?

Five sentences, front-loaded with the core action, and every sentence adds unique value: purpose, usage scenario, integration, algorithm details, and limits. Dense but well structured with em-dashes and semicolons.

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?

No output schema, so the description compensates by explaining the output passages, character offsets, similarity scores, truncation behavior, and pairing with ask_pipeworx_grounded. It is fully self-sufficient for an agent to invoke correctly.

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 coverage is 100%, so baseline is 3. Description adds concrete query examples and clarifies the text param with real-world use cases (SEC 10-K, article, long tool result), plus limit default context. This adds meaningful depth 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 states a specific verb+resource: 'Semantic search INSIDE a fetched record' returning top-N passages. It distinguishes from siblings by contrasting with ask_pipeworx_grounded and emphasizing the in-record scope.

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?

Explicit when-to-use guidance: 'Use when the record is too big to cram into the prompt' and how it saves context. Names ask_pipeworx_grounded as the paired alternative, providing clear integration instructions.

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

All Arcgis Allegheny toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

Multiple tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical, and several Polymarket analysis tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, bet_research) blur together. The three ArcGIS tools are distinct, but they are drowned out by a large set of data-query and prediction-market tools with unclear boundaries.

Naming Consistency3/5

All tool names use snake_case, but the verb/noun pattern is mixed: some are command-style (query_layer, validate_claim), some are noun phrases (layer_info, entity_profile), and others are bare verbs (remember, forget). The naming is readable but not consistently patterned.

Tool Count2/5

34 tools is too many for a server named 'Arcgis Allegheny', especially since only three tools (search_datasets, layer_info, query_layer) relate to ArcGIS at all. The bulk of the tools address unrelated domains like Pipeworx data lookups and Polymarket betting, making the count excessive for the apparent purpose.

Completeness1/5

For a server focused on ArcGIS Allegheny County data, the surface is severely incomplete: only three read-only tools (search_datasets, layer_info, query_layer) cover the domain, and they lack operations like adding, updating, or deleting features. The remaining 31 tools are unrelated to GIS, so the server fails to provide a coherent or complete toolset for its stated purpose.

Resources