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remove_from_watchlist

DestructiveIdempotent

Remove companies from a watchlist. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesWatchlist id.
companiesYesCompany identifiers: domain, name, LinkedIn URL, or Datahyena id.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already indicate destructiveHint=true, and the description's 'Remove' is consistent. However, the description adds no additional behavioral context such as irreversibility, permission requirements, or side effects beyond the annotation. Since annotations cover the safety profile, this is acceptable but not enhanced.

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 extremely concise: 'Remove companies from a watchlist. Free.' It contains no unnecessary words, and the structure is clean. The 'Free.' is somewhat extraneous but does not detract; overall it is highly focused.

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?

The description adequately conveys the core operation, but it does not specify what happens after the removal (e.g., return value or success/failure semantics). Since there is no output schema, this is not required, but a more complete description might mention whether the updated watchlist is returned or if errors are expected. It is sufficient for a simple destructive action but lacks a minor detail.

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 coverage is 100% with descriptions for both parameters. The description for 'companies' adds useful detail about accepted identifier formats ('domain, name, LinkedIn URL, or Datahyena id'), but the 'id' description is minimal ('Watchlist id.'). This matches the baseline for full schema coverage without significant extra value.

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: 'Remove companies from a watchlist.' It names the specific verb and resource, and it distinguishes from sibling tools like add_to_watchlist or create_watchlist. The purpose is unambiguous.

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 (when you need to remove companies) but does not explicitly mention when not to use it or suggest alternative tools. Unlike the HIGH example, it lacks an explicit cross-reference such as 'use add_to_watchlist instead.' The context of sibling tools makes it clear, but the description itself does not provide explicit guidance.

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

A4/5.0
Disambiguation5/5

Each tool targets a clearly distinct resource or action: event types (acquisitions, funding_events, exec_moves), entities (companies, investors), and watchlist operations. The watchlist CRUD commands are separated by function, and company_timeline is clearly scoped to a single company's full history.

Naming Consistency4/5

Watchlist tools consistently use verb_noun (create_watchlist, get_watchlist, add_to_watchlist), while data lookup tools use plural nouns describing the returned entity or event (companies, investors, funding_events). The mixed convention is readable and predictable, with only company_timeline deviating from both patterns.

Tool Count5/5

With 11 tools, the server is well-scoped for its domain: company/event data search plus watchlist management. Each tool has a defined role and the count feels neither sparse nor bloated.

Completeness4/5

The toolset covers the core domain well: company and investor search, major event types, company timelines, and full watchlist membership management. A notable minor gap is the absence of a delete_watchlist tool, since create/list/get/add/remove exist for watchlists.

Resources