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Height of an object seen by several witnesses

triangulate
Read-onlyIdempotent

Estimate the height and distance of one object seen at the same moment by 2 to 6 witnesses, from each witness's position and line of sight, with a height range covering typical compass errors. Use it only when several people measured the same object at the same time; for a single witness use identify or what_did_i_see. Local geometry, no network call; the result is a candidate, never a proof.

Input Schema

NameRequiredDescriptionDefault
sightingsYes2 to 6 sightings, each {lat, lon, az, el}: witness position and measured direction of the object.

Output Schema

NameRequiredDescriptionDefault
statusNo
qualityNo
height_mNo
citationsYes
provenanceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / sightings / description
      Added value: +"2 to 6 sightings, each {lat, lon, az, el}: witness position and measured direction of the object."
    • addedOutput schema / description
      Added value: +"Returns status (candidate | baseline_too_short | no_intersection), height_m, height_range_m_if_sightings_off_by_2deg, distance_from_witnesses_m, quality, interpretation."
  2. Added

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive and closed-world, but the description still adds real context: the computation is local geometry with no network call, the range accounts for typical compass errors, and the output is explicitly "a candidate, never a proof." That uncertainty framing is the kind of disclosure annotations cannot carry; only the error/edge-case behavior for bad sightings is left unstated.

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 dense sentences: capability and witness constraint first, routing to alternatives second, caveats last. No filler, no restatement of the title.

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?

With an output schema present and annotations carrying the safety profile, the description supplies exactly the missing pieces: when to call it, the witness-count requirement, the local-computation fact, and the epistemic caveat on results.

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 the baseline is 3, but the description adds conceptual meaning by mapping the parameters to "each witness's position and line of sight," clarifying that lat/lon are standpoints and az/el are measurements, and it explains why 2-6 items (compass error tolerance).

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?

States a specific verb and output ("Estimate the height and distance of one object") plus the hard constraint of 2 to 6 witnesses, then names the sibling tools (identify, what_did_i_see) it is not. An agent can separate it from the other sighting-related tools without opening any schema.

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?

Gives an explicit inclusion rule ("only when several people measured the same object at the same time") and an explicit exclusion routing to alternatives for the single-witness case. The minimum-witness condition is stated twice, so there is nothing left to infer.

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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