Skip to main content
Glama
Sign In
mesa-clm

mesa-clm

by idss-mesa
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

mesa_avu_apply_datacite

Validate DataCite 4.x records and write metadata as AVUs to iRODS paths, using canonical or CyVerse-template naming, then mirror each result to DuckLake as a snapshot.

Instructions

Validate a DataCite 4.x record and write it to an iRODS path as AVUs (canonical and/or CyVerse-template naming), mirrored to DuckLake as one snapshot.

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": {
      "target": "<target>",
      "record": "<record>"
    },
    "name": "mesa_avu_apply_datacite"
  }
}

Input Schema

NameRequiredDescriptionDefault
namingNocanonical | cyverse_template | bothboth
recordYesA DataCite 4.x record (validated).
targetYesiRODS path of the data-object or collection.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses validation, the AVU write with naming modes, and the non-obvious DuckLake snapshot side effect. It omits permissions/auth requirements, failure behavior, and reversibility, keeping it short of a 5.

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?

One dense sentence with the primary action front-loaded and zero filler. Every clause (validate, write AVUs, mirror) earns its place.

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 mutating pipeline tool with a nested record object and no output schema, the description adequately covers the operations performed. It could mention validation-failure behavior or prerequisites, but nothing critical to invocation is missing.

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 schema already documents target, record, and naming. The description restates the naming variants but adds no format, syntax, or constraint details beyond the schema. 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?

States specific verbs (validate, write, mirror) and resources (DataCite 4.x record, iRODS AVUs, DuckLake snapshot). It is clearly distinguishable from siblings like mesa_datacite_validate (validation only) and ds_add_avus (generic AVU write).

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?

No when-to-use or when-not-to-use guidance is given, and no alternative is named despite several plausible siblings (mesa_datacite_validate, ds_add_avus, mesa_avu_apply_term). Usage must be inferred from the pipeline verbs alone.

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

Deploy Server

Other Tools