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add_project_resources

Add one or more resources to a project.

Webhooks are first-class project resources: a webhook can belong to several projects at the same time, and deleting a project only detaches its webhooks — it never deletes them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoCatchAll API key. Optional if provided via x-api-key header or CATCHALL_API_KEY env var.
resourcesYesA list of resource objects, each `{"resource_type": ..., "resource_id": ...}`. `resource_type` is one of: 'job', 'monitor', 'dataset', 'monitor_group', 'webhook'. May also be passed as a JSON-string array for client compatibility.
project_idYesThe project ID to add resources to.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.1/5.0
Behavior4/5

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

While no annotations are present, the description discloses an important non-obvious behavior: webhooks can belong to multiple projects, and deleting a project only detaches webhooks rather than deleting them. This goes beyond the schema and adds value, though it does not cover all possible side effects like duplicates or validation.

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, with only two sentences. It front-loads the core purpose and then adds a relevant clarifying note about webhooks. Every sentence earns its place, with no redundant information.

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 simplicity of the tool, the schema covers all parameters, and an output schema is present, the description is sufficiently complete. It includes the key nuance about webhook lifecycle that could affect user expectations, making it contextually complete for this operation.

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 description coverage is 100%, so the baseline is 3. The description does not add any additional meaning beyond the schema—it does not elaborate on the structure of 'resources' or the meaning of 'project_id' beyond what is already provided in the input schema.

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 action: 'Add one or more resources to a project.' It identifies the resource type (project resources) and the operation, distinguishing it from sibling tools like 'remove_project_resource' and 'list_project_resources'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context about webhooks as first-class resources but does not explicitly state when to use this tool versus alternatives such as 'assign_webhook_resource' or 'remove_webhook_resource'. The webhook behavior implies usage, but no clear exclusions or comparisons are given.

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.