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cantrip_entity_add

Add new entities like customers, pain points, or experiments to Cantrip's GoToMarket platform to organize and track business development data.

Instructions

Create a new entity. Automatically marked as 'accepted'. Fields vary by type:

  • icp: name, description, demographics, jobs_to_be_done, willingness_to_pay, current_alternatives, priority, is_beachhead

  • pain_point: description, severity (low|medium|high|critical), frequency (rare|occasional|frequent|constant), evidence

  • value_prop: framing (required — use instead of 'name'; 'description' is stored in extensions), tagline, evidence

  • channel: name, channel_type, lifecycle_stage (exploring|testing|scaling|maintaining|killed), cac, estimated_reach, conversion_rate (note: 'description' maps to 'notes' column)

  • experiment: title (required — use instead of 'name'), hypothesis, description, status (proposed|designed|active|completed|analyzed|abandoned), success_metrics, outcome_notes, value_prop_id, channel_id

  • competitor: name, description, url, positioning, strengths, weaknesses, pricing_model

  • contact: name, email, phone, company, role, source, url, notes Extra fields (any field not in the schema above) are stored in extensions. After adding entities, pause and confirm with the user before adding more. Pass project to override .cantrip.json — useful in cloud-hosted or multi-project contexts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_typeYesEntity type: icp, pain_point, value_prop, experiment, channel, competitor, contact
nameNoEntity name (mapped to 'framing' for value_prop, 'title' for experiment)
descriptionNoEntity description
fieldsNoAdditional fields as key-value pairs (e.g. {severity: 'high', frequency: 'constant'})
projectNoProject slug — overrides .cantrip.json. Required in environments where cantrip_connect cannot write to the filesystem.
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 of behavioral disclosure. It effectively describes key behaviors: automatic 'accepted' marking, field variations by entity type, storage of extra fields in extensions, the pause-and-confirm workflow after adding, and the project override capability. It doesn't mention error conditions, rate limits, or authentication requirements, but provides substantial operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately front-loaded with the core purpose, but becomes quite lengthy with detailed field listings for 7 entity types. While all information appears relevant, the bulleted lists make it dense. Some information could potentially be streamlined while maintaining clarity.

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?

For a 5-parameter tool with no annotations and no output schema, the description provides substantial context about entity creation, field mappings, and workflow considerations. It covers the core functionality comprehensively but doesn't describe return values or error responses. Given the complexity of supporting 7 entity types with different field requirements, the description does a good job of providing necessary context.

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?

With 100% schema description coverage, the baseline is 3. The description adds significant value by explaining how 'name' maps to 'framing' for value_prop and 'title' for experiment, clarifying that 'description' maps to 'notes' for channels, and detailing which fields are required for specific entity types. It provides concrete examples of field structures that go beyond the schema's generic descriptions.

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 verb ('Create') and resource ('new entity'), specifying it's automatically marked as 'accepted'. It distinguishes from siblings like cantrip_entity_edit (edit vs create) and cantrip_review_accept (automatic vs manual acceptance). The description provides specific details about entity creation that differentiate it from other 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?

The description provides clear context about when to use this tool (creating new entities) and includes guidance about pausing after adding entities. It mentions using the 'project' parameter to override .cantrip.json in cloud-hosted contexts. However, it doesn't explicitly state when NOT to use this tool versus alternatives like cantrip_entity_edit for existing entities.

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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