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Capture Insight

capture_insight

Record customer feedback as insights or opportunities, linking them to accounts and features for product prioritization. Each capture fires a webhook to keep your workflow in sync.

Instructions

Write a piece of customer feedback to the spine (the agent's own hand, not just reading) and return the created insight. Fires the same insight.created webhook a manual capture does — a real side-effect, so only capture genuine signal. Resolve account_id via get_customer_360 and feature_id via list_features and tie them when known; kind='opportunity' marks a prioritisable ask. Only body is required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesThe verbatim feedback / insight text (the only required field).
kindNo'insight' = raw signal; 'opportunity' = a prioritisable ask (optional).
titleNoShort display title (optional).
account_idNoAccount id it's about, from get_customer_360 (optional).
feature_idNoFeature id to link on the spine, from list_features or pm_meta (optional).
product_idNoProduct id, from whoami (optional; the org's primary product when omitted).
Behavior4/5

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

The description discloses that the tool fires the same insight.created webhook as a manual capture, indicating a real side-effect. This adds behavioral context beyond the annotations (which already mark readOnlyHint=false). It does not contradict any annotations.

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

Conciseness4/5

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

The description is three sentences long, with the main action front-loaded. Each sentence contributes essential information (function, side-effect, parameter guidance). It is efficiently written without extraneous content.

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 the tool has 6 parameters (1 required) and no output schema, the description covers the return value (created insight), side-effect, and parameter sourcing. It is complete enough for a creation tool, though it could elabor on error handling or idempotency, but annotations already address idempotency as false.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage, the description still adds significant value by telling how to source parameter values (e.g., account_id from get_customer_360, feature_id from list_features) and clarifying that kind='opportunity' marks a prioritisable ask. This goes beyond the schema's field 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 uses a specific verb 'Write' and resource 'customer feedback to the spine', clearly distinguishing it from siblings like create_feature or create_task. It also mentions returning the created insight, leaving no ambiguity about the tool's function.

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 explicitly advises to 'only capture genuine signal' and provides guidance on resolving account_id and feature_id from specific tools (get_customer_360, list_features). It explains the role of kind='opportunity', offering clear context for when to use this tool versus other creation tools, though it lacks explicit when-not-to-use statements.

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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