quote_productReturns the deterministic, outcome-only terms for AI Dev Board's Verified Interview Pilot. No candidate or agent is charged; legacy package, sponsorship, and Dossier product IDs are retired from agent commerce.
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | No | The only active value is aidevboard_verified_interview_pilot. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden. It discloses that no candidate or agent is charged and that the result is deterministic and outcome-only, but it does not clarify whether this is a read-only operation, what authentication is required, or what happens on invalid input. The 'outcome-only' phrasing is vague and does not fully guarantee absence of side effects.
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, with the primary purpose stated first. No redundant words, and every sentence adds relevant information. Well-structured and easy to parse.
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 one-parameter tool, the description covers the purpose, active product, and retired IDs. However, it lacks a description of the return format or structure of the 'terms,' and there is no output schema to clarify this. It also does not explain how this tool relates to the broader commerce flow, making it somewhat incomplete.
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?
The schema description already provides 100% coverage by stating the only active value for product_id. The description adds valuable context by mentioning that legacy package, sponsorship, and Dossier product IDs are retired, reinforcing the schema's restriction and giving extra meaning 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 tool 'Returns the deterministic, outcome-only terms' for a specific product (AI Dev Board's Verified Interview Pilot). It distinguishes from siblings by focusing on the pilot and noting legacy product IDs are retired, though it could be more explicit about how it differs from list_products or start_checkout.
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?
Usage is implied: use this to obtain terms for the Verified Interview Pilot. The description notes that legacy package, sponsorship, and Dossier product IDs are retired, which discourages using this tool for those. However, it does not explicitly state when to prefer this over sibling tools like list_products or when not to use it.
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.
Most tools have clear, distinct purposes (e.g., search_jobs vs get_job vs get_similar_jobs). The main ambiguity is between match_jobs and analyze_application_readiness, both of which assess candidate-job fit, though one ranks multiple jobs and the other evaluates readiness for a specific role. The application flow steps are well-separated.
All tool names consistently follow the snake_case verb_noun pattern (e.g., get_company, list_companies, apply_to_job). Even longer names like analyze_application_readiness and compile_job_specific_resume adhere to this convention, with no mixed casing or inconsistent verb styles.
With 20 tools, the server is on the heavier side for a job board, though the breadth of features (search, company info, salary, application, interview tracking, and product sales) partially justifies the count. Some redundancy exists (e.g., get_trending_companies vs list_companies, get_stats vs get_salary_data), making the set feel slightly bloated.
The toolset covers core job search and application workflows, but there is no way to list or track submitted applications, view application status, or withdraw an application. Post-application features are limited to interview outcomes, leaving obvious lifecycle gaps for a candidate-facing job platform.