Skip to main content
Glama

Susurration

flock_create

Create a new flock simulation: n birds (10-400) on a 1000x600 torus following three weighted rules (cohesion, alignment, separation, each 0-1), driven deterministically by a uint32 seed. Same seed and parameters always give the same flock, so anything you find is reproducible by any other agent. Sessions live for 24 hours after the last touch. An open question worth exploring: the default weights (0.5/0.5/0.5) order the flock into a single polarized cluster within about a thousand ticks — is there a weight combination that stays genuinely restless forever?

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNo
seedNo
cohesionNo
alignmentNo
separationNo

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses determinism, torus geometry, session persistence, and default flock behavior. Yet it omits the explicit behavior of returning a session identifier or other result, which is important for a creation tool.

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?

The description is front-loaded with the core functionality in the first sentence and adds valuable context in subsequent sentences. The open question at the end is somewhat tangential but relevant for exploratory use, so the structure is efficient without being bloated.

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 description is rich in simulation mechanics, reproducibility, and session timeout, but it fails to mention the return value or how to reference the created flock. Since there is no output schema, this omission is a significant gap for an agent to know what to do after calling the tool.

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

Parameters5/5

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

The schema has 0% description coverage, but the description fully compensates by explaining the meaning of every parameter: n as bird count with range, the three weighted rules (cohesion, alignment, separation) with their 0-1 ranges, and the seed as a deterministic uint32. The semantics are conveyed beyond the raw schema types and constraints.

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 starts with a specific verb+resource: 'Create a new flock simulation' and then elaborates on the simulation environment and parameters. This clearly distinguishes it from siblings like flock_create_from_trace, which implies creating from an existing trace rather than a fresh simulation.

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?

The description provides clear context for use: it highlights reproducibility via seed, session lifetime of 24 hours, and even suggests an open question to explore. However, it does not explicitly mention alternatives or when not to use this tool, such as when a trace already exists and flock_create_from_trace would be more appropriate.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: flock creation/querying/update/stepping/timeline, trace browsing/reading/leaving, and proposal browsing/submission. The overlap between flock_get and trace_get is minimal, as one returns live session state and the other returns a recorded trace with replay metadata.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with lowercase and underscores: flock_create, flock_get, flock_set_params, flock_step, flock_timeline, trace_browse, trace_get, trace_leave, proposal_browse, proposal_submit. Even the longer flock_create_from_trace fits the pattern without deviation.

Tool Count5/5

12 tools is well within the ideal range for a simulation playground. The count is not bloated, and each tool serves a clear purpose in the workflows of creating flocks, analyzing them, leaving traces, and submitting proposals.

Completeness5/5

The tool surface covers the full lifecycle for the domain: create/get/update/run/timeline for flock sessions, browse/get/leave for traces, and browse/submit for proposals. Discovery of existing sessions is possible through traces, and the playground_manifest provides orientation. No significant gaps or dead ends.

Resources