Enroll a user for company research briefings. The user provides their email and tickers to watch. They get weekly or daily digests with filing signals, earnings facts, and AI interest data. Use this when a user says they want to track companies or get regular updates.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | User email address | ||
| tickers | Yes | Array of stock tickers to watch (max 20) | |
| frequency | No | How often to send briefings (default: weekly) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It states the enrollment action and digest frequency but does not disclose side effects like whether existing enrollments are overwritten, confirmation steps, or data retention. Minimal transparency.
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?
Two concise sentences: the first states the action, the second gives usage context. Every word earns its place; no redundancy.
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 tool with 3 parameters (all described in schema), no output schema, and no annotations, the description covers purpose, inputs, and usage scenario. It could be improved by mentioning return value (e.g., confirmation message) but is otherwise complete.
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 baseline is 3. The description restates 'email and tickers to watch' and mentions 'weekly or daily digests', which aligns with the 'frequency' parameter but adds no new details beyond the schema.
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 states the action: 'Enroll a user for company research briefings.' It specifies inputs (email and tickers) and output (digests). It distinguishes from sibling tools like origin_digest (view digests) by focusing on enrollment.
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 explicitly says when to use: 'when a user says they want to track companies or get regular updates.' It does not mention when not to use or provide alternatives, but the context is clear and actionable.
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.
Each tool has a clearly distinct purpose: company lookup, digest, enrollment, filings index, person career, profile, search, timeline, and transcripts. No overlap in functionality.
All tools follow a consistent 'origin_' prefix followed by a descriptive word. The naming pattern is predictable and uniform across the set.
9 tools is appropriate for a filings and company research server. It covers core functionalities without being overwhelming or sparse.
The tool set covers the full domain of company research: lookup, profile, filings, transcripts, timeline, person career, cross-company search, digest, and user enrollment. No obvious gaps.