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HyperBDR

beacon-mcp

by HyperBDR

query_events

Filter and retrieve raw events by date, project, model, user, and status with pagination. Ideal for inspecting individual errors, user actions, or model behavior.

Instructions

Raw event query with date range, project/model/status/user filters and pagination. Use for inspecting individual events (errors, specific users, model behaviour, prompt previews). By default returns up to 100 rows; pass all: true to disable the limit (use sparingly).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgNoOrganization (tenant) ID. Omit to use the default org from $BEACON_ORG.
fromNoStart date inclusive (YYYY-MM-DD).
toNoEnd date inclusive (YYYY-MM-DD).
projectNoProject name to filter by (exact match). Use 'all' to disable.
modelNoModel name to filter by (substring match). Use 'all' to disable.
userNoUser name or id to filter by (substring match). Accepts source_user_name or source_user_id.
statusNoRestrict to error or success events only.
limitNoMax rows to return (1-500). Ignored when `all` is true.
allNoIf true, return every matching row without a limit. Use carefully — may return large payloads.
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses the default limit (100 rows) and the 'all' flag to disable it, and warns to use sparingly. However, it lacks details on output format, authentication needs, or rate limits.

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 two sentences, front-loads the purpose, and contains no fluff. Every word adds value.

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?

For a tool with 9 parameters and no output schema, the description adequately covers the main filters and pagination behavior but omits output specifics and any behavioral caveats beyond the limit.

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%, so baseline is 3. The description mentions filter categories and pagination but does not add significant detail beyond what the schema already provides for each parameter.

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 'Raw event query with date range, project/model/status/user filters and pagination' and specifies it is for inspecting individual events, distinguishing it from sibling summary tools.

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 explicitly says 'Use for inspecting individual events' and lists example uses. It does not explicitly say when not to use, but the context of summary tools in siblings implies differentiation.

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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