Companies still advertising open roles while having posted nothing new in over six months. Strong evidence of a board nobody tidied up after the hiring finished. Useful for striking dead accounts off a prospect list, or for avoiding applications that will never be read.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavior disclosure. It adds useful interpretive context ('strong evidence of a board nobody tidied up'), but it does not state that the tool is read-only, describe output format, or mention pagination or limits.
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?
Three concise sentences: the first defines the selection criteria, the second explains the signal, and the third gives practical use cases. Every sentence earns its place and the key definition is front-loaded.
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?
The description covers the purpose and practical usefulness of the tool well. It is weaker on the sole parameter's meaning and on alternative routing among siblings, but the low complexity and the inferable return type keep it reasonably 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 0%, and the description completely ignores the 'limit' parameter. The agent only knows it is an optional integer, not what it limits or how it affects results, which is a real gap for a one-parameter tool.
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: companies with open roles but no new posts in over six months. It implies a look-up operation, but there is no explicit verb and no direct contrast with the obvious sibling find_fresh_boards.
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?
It gives concrete use cases: removing dead accounts from a prospect list or avoiding applications that won't be read. However, it never mentions alternatives or says when not to use this tool, so the usage guidance stays implied rather than explicit.
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 answers a clearly distinct question: company-specific verdict, fresh boards, quiet boards, market-level stats, job search, and change tracking. There is no meaningful overlap between tool purposes.
Four tools follow a verb-first pattern (check_company, find_fresh_boards, find_quiet_boards, search_jobs), but hiring_stats is a noun phrase and whats_changed is question-style. The names are readable but not fully predictable.
Six tools is well-scoped for a hiring intelligence server. Each tool covers a distinct aspect of the domain without redundancy or bloat.
The surface covers the core workflows: searching jobs, evaluating a single company, surfacing fresh versus quiet boards, viewing market stats, and monitoring changes. No obvious dead ends or missing critical operations for the stated purpose.