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skeptic_report

Run deterministic checks on time-domain astronomy cases to flag blends, saturation, quality cuts, survey-rhythm aliases, and spacecraft systematics before analysis.

Instructions

Run the Skeptic: deterministic checks for blends, saturation, quality cuts, single-observer data, survey-rhythm aliases, unobserved onsets, TESS spacecraft systematics and more.

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>"
    },
    "name": "skeptic_report"
  }
}

Input Schema

NameRequiredDescriptionDefault
caseYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It does usefully disclose that the checks are deterministic and what categories they cover, but it says nothing about side effects (does it write flags or claims to the case?), runtime, or what the report contains. The 'and more' tail also leaves the check set unbounded for an agent trying to reason about coverage.

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?

One front-loaded sentence in which the action and the check categories come first. The long enumeration is informative rather than padding, though 'and more' is a soft close that weakens the precision of an otherwise crisp list.

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?

For a one-parameter diagnostic tool with no output schema, the description is nearly sufficient: an agent knows it is a deterministic vetting pass over a set of named artifact classes. What holds it back is the absence of any statement about what comes back (pass/fail flags, a report, mutations to the case) and the unmentioned case parameter.

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 description coverage is 0% and the single required parameter 'case' is never mentioned in the description. The agent must infer that it takes a case identifier, and there is no statement of accepted format, whether the case must already exist, or what happens if it is invalid. This is the clearest gap in the definition.

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?

Names the operation (run the Skeptic) and enumerates the specific artifact classes it screens: blends, saturation, quality cuts, single-observer data, survey-rhythm aliases, unobserved onsets, TESS systematics. That is a concrete verb plus a well-scoped resource, clearly distinct from siblings like observer_agreement or periodogram. It stops short of saying what input the checks operate on, which keeps it from a 5.

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 enumerated check list implies the screening/vetting use case without stating when to call it versus alternatives. There is no explicit when-to-use, no prerequisites, and no exclusions such as whether it should be run before registering a claim or after folding a lightcurve. Usage is inferable but not spelled out.

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