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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

get_recovery_recommendations

Read-only

Recommends a recovery strategy for a 3D-printing failure by failure type, with optional printer, material, or saved design context for calibration.

Instructions

Return the historically best recovery strategy (Pro).

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": {
      "failure_type": "<failure_type>"
    },
    "name": "get_recovery_recommendations"
  }
}

Input Schema

NameRequiredDescriptionDefault
brief_idNoOptional saved-goal id from ``design_session`` (or auto-attached at REST dispatch). Surfaces the design's duty / environment / safety so the recovery recommendation can be calibrated to the goal. Default: "".
failure_typeYese.g. ``"adhesion_failure"``, ``"layer_shift"``, ``"filament_runout"``.
printer_nameNoOptional printer filter. Default: "".
material_typeNoOptional material filter (``"pla"``, ``"petg"``, etc.). Default: "".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.1

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already establish that this is a read-only, non-destructive, closed-world operation. The description adds that the recommendation is 'historically best' and gated as Pro, but it does not explain the data source, recency, fallback behavior, or what the returned strategy contains.

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 description is a single front-loaded sentence with no wasted wording. Its brevity is efficient, though it leaves useful routing and output context unstated.

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?

The schema and annotations cover the call mechanics and safety profile, but there is no output schema and the description does not explain the recommendation format. It is minimally complete for invoking the tool but lacks the sibling differentiation and output context an agent would benefit from.

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 description coverage is 100%, so the parameters are fully documented in the schema. The description adds no parameter-specific meaning beyond the schema, which is acceptable at the baseline for high schema coverage.

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 states a clear verb and resource: it returns the historically best recovery strategy. However, it does not distinguish this from the many sibling recovery tools such as get_recovery_plan, plan_failure_recovery, or get_recovery_strategy_stats.

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?

The description gives no guidance on when to use this tool versus the numerous recovery-planning and failure-analysis siblings. The only usage-related hint is the '(Pro)' marker, which suggests a tier restriction but does not explain selection criteria.

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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