CatchAll (by NewsCatcher)

test_webhook

Send a test delivery to a webhook endpoint.

Use when:

You want to verify a webhook URL is reachable and correctly configured before attaching it to a monitor or job.

Input Schema

TableJSON Schema

Name	Required	Description
`api_key`	No	CatchAll API key. Optional if provided via x-api-key header or CATCHALL_API_KEY env var.
`payload`	No	Optional custom JSON object to send as the test body. If omitted, the API sends a default sample payload.
`webhook_id`	Yes	The webhook ID to test.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A3.6/5.0

Behavior2/5

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

No annotations provided, so description bears full burden. It states 'send a test delivery' but omits behavioral details like side effects (e.g., whether a real delivery is attempted), idempotency, restrictions, or error behavior. This leaves the agent uncertain about impact.

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?

Two sentences plus a bulleted 'Use when' section. Action verb first. Every sentence adds value. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given low complexity (3 params, 1 required, no nested objects) and existence of output schema (not shown but indicated), description explains the tool's primary function and use case. Lacks mention of response structure or error cases, but output schema likely covers that.

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. Description adds no extra meaning beyond what schema already provides (e.g., 'optional custom JSON object' repeats schema). No enrichment for parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states action and resource ('Send a test delivery to a webhook endpoint'). Use-case section hints at differentiation from trigger_webhook by focusing on verification before attaching, but does not explicitly contrast with sibling 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?

Explicit 'Use when' guidance specifies verifying webhook URL reachability and configuration before attaching to monitor/job. Does not mention when not to use, but the positive guidance is clear.

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

Disambiguation5/5

Each tool is scoped to a specific resource type and action, with clear distinctions between similarly named operations (e.g., pull_results vs pull_job_csv, initialize_query vs validate_query). No two tools appear to perform the same function.

Naming Consistency4/5

Tools consistently use snake_case verb_noun patterns (create_X, get_X, list_X, update_X, delete_X), with domain-specific verbs like submit, pull, initialize, and validate adding semantic clarity. Minor deviations such as pull_* vs get_* and compound names like create_dataset_from_csv are still predictable.

Tool Count2/5

At 60 tools, the server is heavily overstuffed for a single MCP surface. While the broad domain (datasets, entities, jobs, monitors, projects, webhooks) justifies many operations, the sheer volume exceeds typical recommended limits and includes near-duplicates (pull_results vs pull_job_csv, get_dataset vs get_dataset_status), making agent tool selection unwieldy.

Completeness4/5

The tool set provides robust CRUD and lifecycle coverage for all major resources, including special operations like csv import, webhook mapping, and monitor enable/disable. Minor gaps such as the absence of a get_monitor (single monitor details) and no cancel_job can be worked around via list_monitors and waiting for job completion.

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