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fleet_status

Checks fleet roster against Postgres to detect agent state drift and annotate discrepancies for accurate status verification.

Instructions

Read the canonical fleet roster (fleet.json) — every registered agent and its declared state — annotated with drift diagnostics wherever the fleet Postgres disagrees with the file. Read-only; requires Postgres. Use fleet_health for liveness signals rather than roster membership.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_idYes
Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses 'Read-only' (safety) and 'requires Postgres' (prerequisite), and explains the drift diagnostics output. It does not mention error handling if Postgres is unavailable, but for a read-only roster tool this is reasonably transparent.

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 concise, three sentences, with the primary purpose in the first sentence, constraints in the second, and alternative tool guidance in the third. Every sentence adds value without redundancy.

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 tool is simple (one parameter, no output schema), but the description fails to explain the required app_id parameter. It does give a high-level description of the return content ('every registered agent and its declared state — annotated with drift diagnostics'), but without parameter semantics or error behavior, the overall picture has clear gaps.

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

Parameters1/5

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

The input schema has one required parameter, app_id, with no description, and schema description coverage is 0%. The description never mentions app_id, so the agent has no idea what value to provide or how it affects the results. This is a major gap.

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 'Read the canonical fleet roster (fleet.json)' and specifies the output includes 'drift diagnostics' where Postgres disagrees. It also explicitly distinguishes from the sibling tool fleet_health ('rather than roster membership'), making the purpose unambiguous.

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?

The description provides explicit guidance on when to use this tool versus fleet_health, stating 'Use fleet_health for liveness signals rather than roster membership.' It also gives a prerequisite ('requires Postgres') and notes read-only behavior, giving the agent clear context for invocation.

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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