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Glama

arena_submit

Measure a local Gene in the sandbox and submit its computed fitness to the Arena for ranking; requires rotifer login and a locally installed Gene.

Instructions

Measure a local Gene in the sandbox and submit the measured result to the Arena. Requires authentication (rotifer login) and a Gene that exists locally — use list_local_genes to see them, install_gene to fetch one. The fitness scores are produced by running the Gene, not supplied by the caller: passing fitness_value, safety_score, success_rate, latency_score or resource_efficiency is refused. Runs rotifer arena submit <gene> --cloud.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gene_nameYesLocal Gene name to measure and submit (see list_local_genes)
project_rootNoProject root path (defaults to cwd)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.19.1

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full load and does well: it discloses the auth requirement, that measurement happens server-side by running the Gene rather than being caller-supplied, that certain arguments are rejected, and even the underlying CLI invocation. It stops short of describing what is returned or whether a submission is reversible/overwrites prior results.

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?

Three sentences, front-loaded with the action and scope, then prerequisites, then the refusal rule. Slightly dense but every clause carries information; nothing is padded.

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 two-param tool with no annotations and no output schema, the description covers purpose, prerequisites, alternatives, and the key behavioral constraint. The only real gap is what a successful submission yields (score? URL?), which the agent must infer.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so gene_name and project_root are already documented (baseline 3). The description adds genuine value by enumerating rejected pseudo-parameters (fitness_value, safety_score, success_rate, latency_score, resource_efficiency), which tells the agent the measurement inputs are off-limits despite not appearing in the schema.

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 a specific verb pair (measure, submit) and resource (local Gene -> Arena), which no sibling tool covers. An agent can distinguish this from run_gene, test_gene, or publish_gene without opening a schema.

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

Usage Guidelines5/5

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

Explicitly states the prerequisites (rotifer login, Gene existing locally) and routes to named siblings: list_local_genes to discover, install_gene to fetch. Also states a negative condition — supplying fitness_value and friends is refused — so the agent knows what not to do.

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