get_replay_today
Today's graded candidates timeline (educational replay).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| min_score | No |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Today's graded candidates timeline (educational replay).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| min_score | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It only states 'educational replay', which hints at non-actionable or historical context, but does not explain data recency, scoring semantics, absence behavior, or why a caller might need this versus live tools.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence with no filler. The temporal scope is front-loaded and the 'educational replay' qualifier adds useful context without bloating the definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only timeline with an output schema, the core idea is present, but the description is too thin: it omits parameter semantics and usage routing, and offers no behavioral context that the agent could not infer from the tool name alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description mentions neither limit nor min_score. It does not explain how these parameters affect the returned timeline, leaving the agent to guess from names and defaults alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource: today's timeline of graded candidates, with an 'educational replay' qualifier. This distinguishes it from get_hist_replay on temporal scope, though it lacks a direct verb and leaves 'graded candidates' somewhat ambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given for when to use this tool versus siblings like get_hist_replay, get_morning_desk, or get_latest_alert. The temporal 'today' hint is helpful, but there is no explicit context or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct metric or workflow—alert checks, alert lists, gamma maps, volatility indices, replay timelines, execution plans—so an agent can reliably pick the right one from its description. Even the alert-related tools (get_latest_alert, list_alert_history, check_alert_tradeable) have clearly separate outputs.
All tool names follow a consistent verb_noun snake_case pattern (mostly get_, plus check_, format_, list_, plan_). This makes the set predictable and easy to scan.
At 32 tools, the surface is heavy and approaches a disorganized collection of endpoints rather than a curated set. Many individual get_* indicators could be grouped into a smaller number of dashboard or snapshot tools without losing clarity.
The server covers the core 0DTE intelligence lifecycle: alerts, historical replays, risk overlays, structure, gamma, volatility, news, and advisory planning. Minor gaps exist—such as a direct quote or option chain feed—but they are not essential to the stated purpose.