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

No annotations are supplied, so the description carries the full behavioral burden and largely does not meet it. 'Real-time feed' hints at freshness but says nothing about read-only safety, whether results are cached or live, rate limits, source coverage among the 'leading AI companies', or what happens when no matches exist. An agent cannot predict the operation's side effects or constraints.

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?

One sentence, front-loaded with the topic and scope, with zero filler or repetition. It is efficient, though its brevity stems partly from under-specification rather than disciplined density.

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 simple, single-optional-parameter read tool this is close to adequate, but with no output schema and no annotations the description should indicate what a returned item contains (company, title, location, posting date, URL) and how 'real-time' is sourced. Those gaps leave an agent guessing about result shape and provenance.

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?

There is a single optional parameter (maxResults) whose schema description fully documents it, so the baseline of 3 applies when the schema does the work. The tool description adds no further meaning about the parameter, such as a maximum allowed value or how truncation is handled. No compensation is needed, but no extra value is contributed either.

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 names a specific resource domain (AI, ML, and LLM engineering job openings from 'leading AI companies') and a data type (a 'real-time feed'), which is more informative than the tool name alone. However, 'Radar' and 'feed' are not concrete verbs, so an agent still has to infer that this returns a list of job postings rather than performing a search or scrape. Purpose is recognizable but not sharply stated.

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?

There is no guidance on when to call this versus the numerous sibling hiring tools (e.g., german_jobs_scraper, greenhouse_b2b_tech_hiring_velocity_scraper, greenhouse_fintech_compliance_hiring_tracker). No exclusions, no prerequisites, no mention of what differentiates this AI/ML-focused feed from adjacent Greenhouse monitors. The agent must infer usage entirely from the tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.