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update_monitor

Update a monitor's webhook assignments and per-run limit.

Note: schedule and reference_job_id cannot be modified through this endpoint. Webhooks are centralized — pass webhook IDs (from create_webhook/list_webhooks).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoOptional updated maximum records per run (minimum 10).
api_keyNoCatchAll API key. Optional if provided via x-api-key header or CATCHALL_API_KEY env var.
monitor_idYesThe monitor ID to update
webhook_idsNoOptional list of webhook IDs to assign to this monitor. Pass an empty list `[]` to clear all webhook assignments.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.3/5.0
Behavior3/5

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

With no annotations, the description carries the transparency burden. It discloses mutating behavior and restrictions but omits prerequisites, error handling, and idempotency. The note about webhook centralization adds value, but more detail on side effects or requirements would improve clarity.

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 concise, front-loaded with the purpose, and includes a note and a sentence. Every sentence adds value, with no redundancy.

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?

Given the presence of an output schema, the description adequately covers the tool's functionality, parameter usage, and constraints. It addresses the specific subset of fields that can be updated, making it complete for the intended use.

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

Parameters4/5

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 adds context beyond the schema, such as clarifying that webhook_ids come from create_webhook/list_webhooks and that an empty list clears assignments. This enriches understanding.

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 the tool updates a monitor's webhook assignments and per-run limit. It distinguishes itself from sibling tools like create_monitor, delete_monitor, etc., by specifying the restricted fields (schedule, reference_job_id) that cannot be modified.

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 explains what fields can be updated and notes that schedule and reference_job_id cannot be modified. It also guides on webhook IDs, referencing create_webhook/list_webhooks. However, it does not explicitly state when not to use this tool or provide alternatives for other modifications.

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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TDQS

A3.6/5.0
Disambiguation4/5

Most tools have distinct purposes, but some pairs like create_dataset vs create_dataset_from_csv or pull_results vs pull_job_csv could cause confusion. However, descriptions clarify differences.

Naming Consistency4/5

Tools follow a consistent verb_noun pattern (e.g., create_dataset, list_datasets) with minor exceptions like append_csv_to_dataset and pull_job_csv. Overall predictable.

Tool Count3/5

60 tools is high for an MCP server, but the domain (web research, job processing, multiple resource types) justifies the count. Still borders on excessive.

Completeness5/5

The server offers full CRUD for datasets, entities, monitors, projects, webhooks, plus job submission, status polling, result retrieval (JSON/CSV), webhook management, and health endpoints. No obvious gaps.