Skip to main content
Glama
bdbais

io.github.bdbais/routeai

by bdbais

fleet_nodes

Manage a single machine in the fleet configuration: add, remove, enable, or disable it while preserving other machines' settings, with automatic model probing on add and backup of the previous file.

Instructions

Add, remove, enable or disable ONE machine in the fleet configuration, keeping every other machine's settings and comments. 'add' probes the new server and picks its models per category; 'list' only shows the current machines. The previous file is kept as a backup.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNofor 'add': http://192.168.1.13:11434, or a provider base URL
nameNoshort name of the machine, e.g. gpu
tierNofor 'add' (default: auto, decided by the benchmark)
actionYes
modelsNomodels per category, e.g. {"docs": ["gemini-2.5-flash"]}
num_ctxNo
providerNofor 'add' of a remote AI: fills url and the usual key variable (gemini, groq, openrouter, deepseek, mistral, openai, custom)
cost_inputNoUSD per million input tokens (0 = free tier)
send_filesNomay this project's files be sent to that provider? ask the user first
api_key_envNoname of the environment variable holding the key - never paste the key itself
cost_outputNoUSD per million output tokens
daily_tokensNo
max_parallelNo
daily_cost_usdNostop using this provider after this much per day
daily_requestsNofree-tier or self-imposed daily request cap

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does reveal that changes are scoped to one machine, that a backup of the previous file is kept, and that 'add' involves network probing. However, it does not specify side effects for remove/disable (e.g., whether data is deleted), potential permission requirements, or reversibility beyond the backup, leaving gaps in transparency.

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?

The description is three sentences, front-loaded with the core action and scope. Each sentence adds substantive detail: preservation of other machines, action-specific behavior for add/list, and backup safety. No filler or redundancy, achieving high information density per word.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 15 parameters, no output schema, and no annotations, the description is notably incomplete. It doesn't explain the full behavior of remove/enable/disable actions, doesn't map parameters to actions, and omits details like required fields per action or error conditions. An agent would still need to infer a lot to call the tool correctly across all scenarios.

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?

The description adds meaningful context for 'add' (probes server, picks models) and 'list' (shows current machines), which helps interpret those parameters. But it does not clarify which parameters apply to which actions (e.g., that remove only needs name), nor does it compensate for the parameters lacking schema descriptions (num_ctx, daily_tokens, max_parallel). Schema coverage is 73%, so the description adds partial value but isn't sufficient to fully clarify conditional parameters.

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 clearly states the tool manages ONE machine in the fleet configuration with specific actions (add, remove, enable, disable) and explicitly scopes its effect by preserving other machines' settings and comments. This distinguishes it from sibling tools that likely perform fleet-level operations, making the purpose unmistakable.

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 provides no explicit guidance on when to use this tool versus alternative fleet tools like fleet_setup or fleet_status. It mentions 'list' but doesn't contrast it with potential listing alternatives. There are no when-not-to-use conditions or references to sibling tools, leaving the agent to infer usage context.

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