company_timelineChronological lifecycle event list for any company — founding year, SEC former-name rebrand events, current status, parent disclosures.
| Name | Required | Description | Default |
|---|---|---|---|
| lei | No | Resolve subject by GLEIF LEI. | |
| domain | No | Resolve subject by domain. | |
| ticker | No | Resolve subject by ticker. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already communicate that the tool is read-only, idempotent, open-world, and non-destructive. The description adds useful content-level context, such as SEC former-name rebrand events and parent disclosures, but it does not disclose behavior around the three optional identifiers, such as precedence when multiple are provided or whether the list is ordered differently.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with the core concept front-loaded before the em dash and supporting examples after. Every element earns its place, and there is no redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only event-list tool without an output schema, the description names the expected output categories well enough for an agent to understand what it returns. It does not cover disambiguation behavior among the three optional resolvers, but the schema and annotations already cover parameter and safety aspects, so the remaining gap is minor.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are already fully documented in the schema. The description adds no parameter-specific semantics beyond what the input schema provides, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource (a chronological lifecycle event list for a company) and names specific content: founding year, SEC former-name rebrand events, current status, and parent disclosures. It is specific enough to convey the tool's purpose, though it does not explicitly differentiate it from siblings like company_enrich or company_change.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used to obtain a company's lifecycle events, but it provides no explicit when-to-use guidance or alternatives. With a large sibling list including company_change, company_insights, and company_enrich, an agent is given no criteria for choosing this tool over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have genuinely blurry boundaries: company_change vs company_changes differ only by singular/plural yet serve different purposes, company_domain vs company_classify vs company_lookup_auto all accept a domain, geo_zip_lookup vs geo_enrich vs geo_zip_batch all return ZIP profiles, and email_validate subsumes much of email_disposable and email_free_provider. The domain prefixes help narrow search space, but within many domains an agent cannot reliably predict which tool is the right one.
All 129 tools uniformly follow a snake_case [domain]_[topic] convention (company_, fx_, geo_, dns_, weather_, tax_), which is highly predictable and consistent. Minor deviations include the confusing company_change/company_changes pair, and inconsistent suffix usage (_batch appears on address_validate_batch, company_domains_batch, geo_zip_batch but not on equivalent lookup tools elsewhere).
129 tools far exceeds the 50+ extreem-mismatch threshold, bundling roughly 28 unrelated data domains (weather, fx, tax, ccompany, dns, jobs, flight, email, phone, tax...) into a single MCP surface. Even focusing on one domain forces the agent to load an enormous unrelated tool list; this should be split into many smaller domain-specific servers.
Per-domain coverage is impressively thorough: weather spans current/forecast/hourly/historical/normals/marine/route/air-quality, fx covers rates/convert/historical/volatility/correlation/strenth, and company includes lookup/enrichment/networks/timeline/peer-comparison plus six buyer-tuned signals with profile-introspection tools. Minor gaps like flight being historical-only and smtp probes skipping major email providers are documented scope decisions rather than dead ends.