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by morluto
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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analyze_nsight_compute

Read-onlyIdempotent

Analyze persisted Nsight Compute rule facts to audit GPU kernel qualifications, coverage, and data provenance. Use recapture suggestions to gather missing evidence without reopening .ncu-rep files.

Instructions

Analyze persisted Nsight Compute rule facts without reopening the native .ncu-rep.

The bounded result includes target qualification, coverage, provider provenance, and a concrete recapture selection when more evidence is needed.

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": {
      "run_or_artifact": "<run_or_artifact>",
      "limit": "<limit>"
    },
    "name": "analyze_nsight_compute"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitYesMaximum provider rule findings to return.
run_or_artifactYesRun or artifact ID; discover one with list_runs or list_artifacts.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.15

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the description does not need to restate safety. It adds value by disclosing that the result is bounded and what it contains (qualification, coverage, provenance, recapture selection), plus the external behavior of not reopening the .ncu-rep. No contradiction with annotations.

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 sentences, front-loaded with the core action and followed by a compact result summary. No filler or redundant restatement of parameters.

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?

With a full input schema, output schema, and annotations, the description is sufficient: it explains the tool's scope and result shape. It could name the upstream extraction sibling or define 'rule facts', but this is not necessary for choosing or invoking the tool.

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%: both parameters (limit, run_or_artifact) are described in the schema, including discovering IDs via list_runs/list_artifacts. The description adds no additional parameter-specific semantics beyond the schema, so baseline 3 applies.

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?

The description identifies a specific verb ('Analyze'), a specific resource ('persisted Nsight Compute rule facts'), and an operative constraint ('without reopening the native .ncu-rep'). This distinguishes it from extraction-oriented siblings such as extract_nsight_compute, even without naming them.

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

Usage Guidelines4/5

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

The phrase 'persisted ... without reopening the native .ncu-rep' gives a clear context: use this after facts are already persisted, rather than for direct native-file extraction or recapture. It doesn't enumerate exclusions or alternative tool names, but the context is strong enough to route an agent.

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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