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get_webhook_history

Get webhook delivery history, either for a resource or for a webhook.

Query in exactly one of two modes:

  • By resource: pass resource_type + resource_id to see deliveries made for a specific job/monitor/monitor_group.

  • By webhook: pass webhook_id to see every delivery made through one webhook — including manual test deliveries (from test_webhook), which are not tied to a job or monitor and only appear in this mode.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for pagination (default: 1).
api_keyNoCatchAll API key. Optional if provided via x-api-key header or CATCHALL_API_KEY env var.
page_sizeNoNumber of results per page (default: 50, max: 500).
webhook_idNoWebhook ID to fetch history for. Mutually exclusive with `resource_type`/`resource_id`.
resource_idNoThe ID of the job/monitor/monitor_group.
resource_typeNoResource type: 'job', 'monitor', or 'monitor_group'. Required together with `resource_id` when `webhook_id` is not given.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: mutual exclusivity of parameters, the requirement to pass resource_type+resource_id together, and the important nuance that manual test deliveries are only visible in webhook mode. This goes beyond basic reading behavior, though it does not address potential error behavior 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 front-loaded with the purpose, then presents the two modes in a clear, scannable bullet-like structure. Every sentence provides necessary context—no fluff or repetition. It is concise yet complete.

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?

The tool has 6 optional parameters and two mutually exclusive modes. The description resolves the main ambiguity (modes) and adds a valuable behavioral nuance (manual test deliveries). Since an output schema exists and parameter schema coverage is 100%, the description appropriately focuses on the decision logic and mode-specific behavior, making it fully complete for this tool's complexity.

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 the baseline is 3. The description adds meaningful semantic grouping by explaining how the parameters interrelate: webhook_id is mutually exclusive with resource_type/resource_id, and the latter two must be used together in resource mode. This supplements the schema's individual property descriptions with mode-level context.

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 specific verb+resource: 'Get webhook delivery history', and immediately distinguishes two query modes (by resource or by webhook). This differentiates it from sibling tools like get_webhook and list_webhooks, which focus on webhook configuration or listing rather than delivery history.

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 provides explicit when-to-use guidance by mandating 'exactly one of two modes' and detailing which parameters to pass for each. The note about manual test deliveries only appearing in webhook mode clarifies a non-obvious use case. However, it does not explicitly name alternative tools or state when NOT to use this tool, just missing the highest tier.

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.