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alexwoolford

SEC Ownership Graph

by alexwoolford

activist_coalition

Read-onlyIdempotent

Find the de-facto activist coalition around a 13D filer, linking co-targeting activists while excluding custodial hubs. Returns member list and coalition diameter.

Instructions

Find the de-facto activist coalition (wolf-pack) around a named 13D filer.

Two activists are linked when they co-target >=min_shared_targets of the same issuers via 13D. Custodial/broker hubs are scrubbed before the connected component is formed (precision discipline), so the coalition reflects coordinated activists, not shared custodians. Returns members + coalition diameter. Abstains when the filer sits in no multi-member coalition (or was scrubbed as a custodial hub).

Example: activist_coalition("ICAHN CARL C") -> the ~22-member scrubbed cluster (Bulldog/Goldstein, GAMCO/Gabelli, Karpus, Icahn, Dolan family).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
activistYes
min_shared_targetsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already convey read-only and non-destructive behavior. The description adds valuable algorithmic details: scrubbing of custodial/broker hubs, the precision discipline, and abstention behavior. It clearly explains what the tool does internally, going beyond the safety 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?

The description is well-structured and front-loaded with the core purpose. The three sentences cover purpose, methodology, and abstention, followed by an illustrative example. No wasted words; every sentence contributes to understanding.

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?

With an output schema present, the description need not detail return shape, but it still mentions 'Returns members + coalition diameter.' The tool's complexity is moderately high, and the description covers the key behavioral aspects, edge cases, and parameter semantics, making it complete for an agent.

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?

Schema description coverage is 0%, so the description must compensate. It explicitly explains both parameters: 'activist' is the named filer (illustrated in the example), and 'min_shared_targets' is the threshold for linking activists. The description fully covers parameter meaning, going beyond the bare 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 opens with a specific verb+resource: 'Find the de-facto activist coalition (wolf-pack) around a named 13D filer.' It clearly distinguishes what the tool does and includes a concrete example, making the purpose unambiguous even without explicit sibling differentiation.

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 when to use the tool (to find coalitions around a filer) and provides an edge-case condition ('Abstains when the filer sits in no multi-member coalition'), but it does not explicitly mention alternative tools or when-not-to-use scenarios. Usage is inferred rather than explicitly contrasted with siblings.

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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