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Hydrata - ANUGA Flood Simulation

by com.hydrata

start_simulation

Start a flood simulation run for a built scenario.

The scenario must be in 'built' status. Returns 202 with the new run. The run transitions through: built → queued → computing → processing → complete.

After starting, poll get_run_status to track progress. Returns 409 if the scenario is not in the correct state.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scenario_idYesThe scenario ID to run
compute_backendNoCompute backend: 'local' (Celery), 'ec2' (dedicated instance), or 'batch' (AWS Batch spot, cheapest). Default: 'local'local

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries full burden. It discloses return status codes (202, 409), the full state transition sequence (built → queued → computing → processing → complete), and the need to poll. This is thorough behavioral disclosure.

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?

Four sentences, front-loaded with purpose, and every sentence adds value (state requirement, status code, lifecycle, polling advice). No fluff or repetition.

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

Completeness5/5

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

Given the tool's complexity, the description covers preconditions, lifecycle, failure mode, and next step. The output schema exists for return details, and sibling tools like get_run_status are referenced. Complete for an informed agent.

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 coverage is 100% with both parameters fully described. The tool description adds no extra parameter semantics beyond restating the built-status requirement, so the baseline of 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?

The description clearly states 'Start a flood simulation run for a built scenario' with a specific verb and resource. It distinguishes from sibling tools like cancel_run and get_run_status by focusing on initiation and referencing the run lifecycle.

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

Usage Guidelines4/5

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

Provides clear context on when to use: requires scenario in 'built' status and advises polling get_run_status afterward. It does not explicitly mention when not to use or directly compare with retry_run, but the guidance is strong.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: project listing vs. details, run polling vs. full details, and separate lifecycle operations (start/cancel/retry). No two tools overlap in purpose.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (list_projects, get_run, start_simulation) with clear verbs. The compound get_run_status is still predictable.

Tool Count5/5

9 tools is a well-scoped size for a domain focused on managing flood simulation runs. Each tool covers a necessary operation without redundancy.

Completeness4/5

The run lifecycle is complete: start, poll, retrieve results, cancel, retry. Minor gap is the lack of scenario creation or building tools, but the server appears to operate on pre-existing scenarios.

Resources