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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

analyze_print_failure

Read-only

Diagnose failed 3D print jobs using job records, events, and printer state to surface likely causes, symptoms, and next steps.

Instructions

Analyze a failed print job and suggest possible causes and fixes.

Examines the job record, related events (retries, errors, progress),
and printer state at the time of failure to produce a diagnosis.

Args:
    job_id: The failed job's ID from ``job_history`` or ``job_status``.

Returns a structured analysis with likely causes, observed symptoms,
and recommended next steps.

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": {
      "job_id": "<job_id>"
    },
    "name": "analyze_print_failure"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYesThe failed job's ID from ``job_history`` or ``job_status``.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.5.1
    • addedInput schema / properties / job_id / description
      Added value: +"The failed job's ID from ``job_history`` or ``job_status``."
  2. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare read-only, non-destructive, closed-world behavior, and the description adds real context beyond that: which data sources are consulted (job record, retries/errors/progress events, printer state at failure time) and the shape of the output (likely causes, symptoms, next steps). It does not disclose cost, latency, or whether the analysis is limited to historical data versus live state.

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?

The purpose is front-loaded in the first sentence, followed by a compact statement of inputs examined and output produced. The trailing Args section duplicates the schema description verbatim and is the only wasted text.

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, read-only analysis tool with no output schema, the description covers the essential ground: what it inspects, what it returns, and where the identifier comes from. The remaining gap is sibling disambiguation in a very crowded diagnosis tool family, which is mild for a tool this simple.

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% for the single job_id parameter, so the baseline is 3. The description simply repeats the schema's own wording ('The failed job's ID from job_history or job_status') rather than adding new meaning such as format expectations or behavior on unknown/queued job IDs.

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 opens with a specific verb+resource ('Analyze a failed print job') and spells out what is examined and produced, so the agent knows exactly what the tool does. It never differentiates itself from near-identical siblings such as analyze_print_failure_smart, diagnose_print_failure_live, get_print_diagnostic, or troubleshoot_print_issue, which keeps it out of 5 territory.

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?

Usage is only implied: the agent must infer that this is a post-failure, offline diagnosis on a job that already failed. It does helpfully state that the job_id comes from job_history or job_status, but there is no explicit statement of when to choose this over the live/smart/diagnostic variants, and no exclusions.

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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