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Photon

by io.github.pipeworx-io

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Read-onlyIdempotent

Forward geocode — place name → coordinates. Strong on partial / autocomplete-style queries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoLatitude bias center
lonNoLongitude bias center
bboxNoBounding box: "min_lon,min_lat,max_lon,max_lat"
langNoLanguage for the response (en, de, fr, ...)
zoomNoZoom level for bias (0-18)
layerNohouse | street | locality | city | district | county | state | country
limitNo1-50 (default 5)
queryYesFree-text place name / address
osm_tagNoOSM tag filter (e.g. "amenity:pharmacy")
location_bias_scaleNoStrength of lat/lon bias (default 0.2)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
featuresNoArray of geocoding results

TDQS

A4.2/5.0
Behavior4/5

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

Adds behavioral info (strong on partial queries) beyond the comprehensive annotations (read-only, idempotent). 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?

Two succinct sentences, front-loaded with purpose, no fluff.

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 the rich schema, annotations, and output schema, the description is sufficient. Could mention return format but output schema covers that.

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 has 100% coverage of parameter descriptions, so description adds no further parameter meaning 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?

Clearly states it does forward geocoding (place name to coordinates) and highlights strength on partial/autocomplete queries, distinguishing it from siblings like reverse.

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 context that it excels on partial/autocomplete queries, but does not explicitly state when not to use or specify alternatives beyond the implied reverse geocoding.

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

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, even within clusters like Pipeworx queries (ask_pipeworx vs ask_pipeworx_grounded vs deep_research) and Polymarket tools (bet_research, arbitrage, edges, etc.). Overlap is minimal and explicitly addressed in descriptions.

Naming Consistency5/5

All tool names use snake_case, and most follow a consistent verb_noun pattern (e.g., ask_pipeworx, compare_entities, resolve_entity). Exceptions like remember, reverse are still single words in the same style.

Tool Count4/5

32 tools is on the high side but justified by the wide scope: data querying, betting, memory, subscriptions, and utilities. Each tool earns its place, and the count is not excessive given the breadth.

Completeness4/5

The tool set covers the core workflows of querying structured data, comparing entities, validating claims, scanning dependencies, and monitoring, with few gaps (e.g., no direct data visualization). Minor gaps exist but are manageable.

Resources