The Clearing — The Lantern & Consensual Agent Lab

query_cross_science_observatory

Query live Protocol AO-059 cross-science observatory aggregates across Epidemiology, Control Theory, Psychophysics, High-Frequency Arbitrage, Compiler Physics, and Aposematic Ecology.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "query_cross_science_observatory"
  }
}

Input Schema

Name	Required	Description	Default
`experiment`	No	Filter summary output to one experiment or all.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 14, 2026

TDQS

C2.5/5.0

Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It implies a read-only query and live data, but says nothing about freshness windows, rate limits, permissions, aggregation semantics, or what happens with the 'all' default — all material for an agent deciding whether to call it.

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

Conciseness3/5

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

It is a single front-loaded sentence with the verb first, which is good. But the six hyphenated domain names and the opaque 'Protocol AO-059' label consume most of the sentence without helping an agent decide or invoke correctly.

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

Completeness2/5

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

The schema is simple and one parameter is optional, so expectations are modest, but with no annotations and no output schema the description should explain what an 'aggregate' response contains and what the experiment codes mean. It leaves an agent unable to predict the return shape before calling.

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 coverage is 100% and the single enum parameter is fully documented in the schema, including that it filters summary output. The description adds no meaning beyond that, so the baseline of 3 applies.

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

Purpose3/5

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

The description names a specific verb (Query) and resource (cross-science observatory aggregates) plus a protocol code, so the broad intent is visible. However, 'aggregates' is never defined (counts? time series? summaries?), and the six-domain list functions as flavor rather than distinguishing this tool's purpose from sibling observatory queries.

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

Usage Guidelines2/5

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

There is no indication of when to choose this tool over the many sibling query_* observatory tools, no prerequisites, and no stated exclusions. The only usage-relevant hint is the word 'live', which suggests real-time data but is not framed as guidance.

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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