oddsky

describe_series

Summarize a time-domain series with summary statistics, long-term slope, and the most significant level change, including when, size, and direction.

Instructions

Summary statistics, long-term slope, and the single most significant change in level (a changepoint: when, how big, which direction) for one series.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "case": "<case>",
      "series": "<series>"
    },
    "name": "describe_series"
  }
}

Input Schema

Name	Required	Description	Default
`case`	Yes
`series`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.1Nov 12, 2026

TDQS

B3.1/5.0

Behavior3/5

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

No annotations exist, so the description carries the full burden. It does disclose meaningful behavior about the result — notably that only the single most significant changepoint is reported, not all of them — but it says nothing about read-only safety (only implied by 'describe'), error behavior for an unknown case or series, or cost/latency.

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?

A single well-formed sentence with the outputs front-loaded and an inline gloss defining the changepoint and its three attributes. No filler.

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?

There is no output schema and no annotations, so the description's sketch of return values (stats, slope, changepoint) is genuinely necessary and helpful. But with two undocumented required parameters and no usage framing, an agent still cannot confidently supply arguments or pick this tool over its many siblings.

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

Parameters2/5

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

Schema coverage is 0%, so the description must compensate and largely fails: 'for one series' only weakly hints that 'series' selects a single series, and the 'case' parameter is never explained at all. Neither expected format nor identifier conventions are given.

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 names the specific computations — summary statistics, long-term slope, and a single changepoint with time, magnitude, and direction — for one series. That is far more specific than a generic 'describe' and distinguishes it from siblings like compare_windows or find_excursions, though it never states the operation as a verb.

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 guidance on when to choose this over alternatives such as compare_windows (which presumably compares two series or windows) or periodogram. No preconditions, no mention of what a caller needs before invoking it, and no exclusions.

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