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compute_access

Calculate time intervals when a satellite is visible from a ground location, applying geometric constraints like elevation and off-nadir angles.

Instructions

Compute access windows (visibility periods) between a satellite and a ground location.

Finds time intervals when a satellite is visible from a location, subject to geometric constraints (elevation, off-nadir, look direction, etc.).

Use list_access_options() to see constraint types, satellite input formats, and configuration options.

Args: location: Ground location dict with lon, lat, and optional altitude_m/name. satellite: Satellite spec dict. Must include "source" key ("tle", "gp_record", or "state"). search_start: Start of search window (ISO epoch string). search_end: End of search window (ISO epoch string). constraints: List of constraint spec dicts. Each needs a "type" key. constraint_logic: How to combine constraints: "all" (AND) or "any" (OR). min_elevation_deg: Convenience shortcut to add an elevation constraint. property_computers: List of property computer specs (e.g. [{"type": "range"}]). config: Optional AccessSearchConfig overrides dict.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
configNo
locationYes
satelliteYes
search_endYes
constraintsNo
search_startYes
constraint_logicNoall
min_elevation_degNo
property_computersNo
Behavior3/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It explains the tool's purpose and parameters but does not discuss side effects, rate limits, or authorization needs. It neither contradicts nor adds significant behavioral context beyond the functional description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear summary and an Args section. It is somewhat lengthy but every sentence adds value given the tool's complexity. It is front-loaded with the main purpose, making it efficient for quick scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (9 parameters, nested objects, no output schema), the description covers parameters well but omits the return format. It directs users to list_access_options() for additional context, which serves as a partial substitute for missing details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must fully explain each parameter. It does so thoroughly in the Args section, including details like expected keys for location, required source key for satellite, and constraint structure. This adds substantial meaning beyond the bare schema types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it computes visibility periods between a satellite and a ground location. It provides a specific verb and resource, but does not explicitly differentiate from sibling tool compute_access_from_gp, though it implies flexibility in satellite input format.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

The description advises using list_access_options() to learn about constraints and config options, which is helpful. However, it does not specify when to prefer this tool over alternatives like compute_access_from_gp, nor does it mention prerequisites or the need for a valid satellite source.

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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