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List signals

list_signals
Read-only

List buying-intent signals SignalRaven detected for your workspace — each a scored LinkedIn moment (a reaction, a hiring trend, a keyword post) with the person, why it matters, and a suggested opener. Newest first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter by signal type (e.g. KEYWORD_SEARCH_REACTION, COMPANY_HEADCOUNT_TREND).
limitNoMax signals to return (1–100).
offsetNoPagination offset.
minStrengthNoOnly signals with strength ≥ this (0–10).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
ctaNoPresent in sample mode: how to get live data.
dataYesThe result rows, newest first.
modeYeslive: the caller's workspace. sample: illustrative data for accounts without an approved workspace.
totalNoTotal rows available, for pagination.
noticeNoPresent in sample mode: explains that the data is illustrative.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and destructiveHint, covering the safety profile. The description adds useful behavioral context: workspace scoping, newest-first ordering, and the anatomy of each signal (person, why it matters, suggested opener). No contradiction with annotations.

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?

A single, well-structured sentence that front-loads the action and resource, then adds the most decision-relevant details. Every clause earns its place; there is no filler or repetition.

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 read-only annotations, complete parameter documentation, and presence of an output schema, the description is nearly sufficient. It explains what makes these signals distinct and the ordering, though it could briefly note that optional filters are available.

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 input schema fully documents all four optional parameters including defaults, ranges, and filter semantics. The description adds no parameter-level detail, but the baseline of 3 applies because the schema carries the burden.

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 ('List') and a clear resource ('buying-intent signals SignalRaven detected for your workspace'). It also describes the output contents and ordering, distinguishing it from the singular get_signal and from list_intelligence.

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 implies usage: call this to get the workspace's detected signal feed, newest first. However, it does not explicitly state when to use it versus alternatives like get_signal or list_intelligence, nor does it mention exclusions.

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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