Skip to main content
Glama

plot_psth

Plots population PSTH per group (mean ± SEM across trials) with a unit-by-time heatmap of change from baseline, returning the PNG path and image.

Instructions

Figure: population PSTH per group (mean ± SEM over trials) above a unit-by-time heatmap of change from baseline. Same arguments as get_psth. Returns the PNG path and the image.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bin_sNo
eventNo
unitsNo
t_afterNo
group_byNo
t_beforeNo
session_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the return value ('Returns the PNG path and the image') and the figure composition. However, it does not mention side effects like saving a file to disk, whether it displays the figure, whether it overwrites existing files, or whether an open session is required. This is a moderate disclosure gap for a plotting tool without annotations.

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 a compact two-sentence structure: the first sentence describes the figure content, the second states arguments and return value. There is no filler, redundant phrasing, or repetition of schema details. The key information is front-loaded, making it easy for an agent to scan.

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 explains the return value and the general figure layout, which covers some essentials. However, with no output schema,nor annotations, and 7 parameters all undocumented, the description is incomplete for an agent that needs to correctly set arguments like group_by, units, or event. The cross-reference to get_psth is a partial mitigation but does not make the tool self-contained.

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

Parameters2/5

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

With schema description coverage at 0%, the description must compensate for parameter meanings, but it only says 'Same arguments as get_psth.' This cross-reference does not explain any of the seven parameters (bin_s, event, units, t_after, group_by, t_before, session_id) and adds no semantic value over the bare schema titles. If get_psth's own description is well-documented, the reference could help, but on its own this is insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the tool's output: a figure combining a population PSTH per group (mean ± SEM) with a unit-by-time heatmap of change from baseline. This lets an agent distinguish it from siblings like plot_raster or plot_probe, though it lacks an explicit verb like 'plots' (only the tool name implies the action).

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

Usage Guidelines3/5

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

The description gives some context by stating 'Same arguments as get_psth,' implying this tool is the plotting counterpart of get_psth)Skip this. It does not explicitly state when to prefer this over alternatives such as plot_raster or plot_latent_factors, nor does it provide any when-not-to-use conditions. The use case is inferable from the figure description but not made explicit.

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