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omniseek_sensor

Monitor a query over time and get notified only when new results appear. Create standing searches with scheduled checks, alert on new or missing items, and manage sensors via run, list, or delete.

Instructions

Use WHEN you want to MONITOR a query over time and be told only what's NEW — standing queries with novelty detection. ONE verb; action picks what to do.

The agent decides WHAT to monitor (judgment); the sensor diffs mechanically (a (source, source_id) fingerprint diff against baseline). Each action's REQUIRED args:

• action="create" (query; optional sources, schedule, notify) -> register a standing query that detects NEW results over time. Sensors run on their schedule automatically in the live service (hourly | daily | weekly; unknown = daily); use action="run" to trigger one manually. Returns the created sensor with its id. notify=True means the scheduler alerts when a scheduled run finds new results; optional notify_if=[keywords] narrows that alert to ONLY new results whose title/content match (notify_if_match="any" default, or "all"), so a broad standing query alerts on the sliver you care about instead of every new item. Optional detect_absence=True ALSO alerts when a tracked STABLE-source item DISAPPEARS (e.g. a page_watch policy page that goes dark / 404s); scoped to stable sources so a churny query sensor is unaffected. • action="list" -> all registered sensors with last-run stats {id, query, sources, schedule, last_run_at, last_new_count, total_runs, baseline_size}. • action="delete" (sensor_id) -> delete a sensor by id. Returns {deleted: true/false}. • action="run" (sensor_id) -> manually trigger one sensor NOW (the manual path beside the automatic scheduler): runs its query, diffs against baseline, updates state, returns a summary with new_count + new_titles. Tests a sensor on demand without waiting for its schedule.

Unknown action, or a missing required arg, returns {"error": ...}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
actionYes
notifyNo
sourcesNo
scheduleNodaily
notify_ifNo
sensor_idNo
detect_absenceNo
notify_if_matchNoany

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.0

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description takes on full behavioral disclosure. It describes automatic scheduling with defaults (hourly | daily | weekly; unknown = daily), manual run behavior, diff against baseline, notification narrowing, absence detection, deletion semantics, and error returns for unknown actions or missing required args.

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?

Despite being long, the text is tightly organized with a front-loaded purpose statement, a clear 'ONE verb' framing, and bullet-per-action structure. Every sentence adds operational detail needed to invoke the tool correctly, so the length is justified.

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?

For a multi-action monitor tool with no output schema, no annotations, and a bare input schema, the description is complete: it covers all actions, required arguments, optional arguments, defaults, return shapes, and error behavior. An agent can determine how to create, list, delete, run, and configure notifications without external information.

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?

Schema coverage is 0%, so the description is solely responsible for explaining the 9 parameters. It does so action by action: required args for create, list, delete, and run, plus optional behaviors for sources, schedule, notify, notify_if, notify_if_match, and detect_absence, and sensor_id usage.

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 opens with a concrete verb-resource pairing: MONITOR a query over time and be told only what's NEW, i.e. standing queries with novelty detection. It also explains that `action` selects the sub-operation, making the tool's role distinct from one-off search or read siblings.

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?

It explicitly states when to use the tool (when you want to monitor over time and see novelty), and it details each action's use case, including manual triggering vs automatic scheduling. It does not explicitly name alternatives or say when not to use it, so it stops one step short of a 5.

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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