check_agent_policy
Check robots.txt, llms.txt, security.txt, and agent.json for crawl/discovery signals before an agent touches a site.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain to check, e.g. example.com |
Check robots.txt, llms.txt, security.txt, and agent.json for crawl/discovery signals before an agent touches a site.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain to check, e.g. example.com |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are empty, so the description must cover behavioral traits. It does not state whether the tool is read-only, whether it respects robots.txt directives, or if it fetches files from the remote server. This lack of detail leaves important behavioral ambiguity for an agent.
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 of 12 words, perfectly concise and front-loaded with the key information. Every word is necessary and no fluff exists.
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 tool is simple with one parameter and no output schema. The description covers the input and the files checked but omits what the output will look like or how results are structured, leaving the agent to guess the return format.
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 coverage is 100% for the single parameter 'domain'. The description adds no further meaning beyond the schema's description ('Domain to check, e.g. example.com'), which is already clear. Baseline score of 3 is appropriate.
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 verb 'check' and the specific resources (robots.txt, llms.txt, security.txt, agent.json). It conveys the purpose of retrieving crawl/discovery signals for a domain. However, it does not explicitly differentiate from sibling tools like agent_security_policies, which have similar scopes.
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 usage 'before an agent touches a site', giving context. However, it offers no guidance on when not to use it or mention alternatives among siblings, leaving the agent to infer when this tool is the best choice.
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.
Tools cover very diverse domains (weather, FDA, legal, crypto, etc.), so cross-domain confusion is low. However, within domains there is notable overlap: multiple food recall tools (food_recall_check, food_safety), multiple weather tools (weather_current_global, weather_forecast_grid, weather_alerts, weather_bias), and several Polymarket-related tools. This can cause agent misselection.
Naming is inconsistent: some tools use verb_noun (search_arxiv, scrape, validate_agent_manifest), others use noun phrases (smart_money, space_weather, tide_data), and some are long descriptive phrases (cross_platform_arb_scan, polymarket_event_scan). No single pattern is followed, making predictions difficult.
95 tools is excessively high for any coherent purpose. The server appears to be a random aggregation of APIs with no clear scope. Such a large catalog overwhelms agents and dilutes utility; most tools could be split into specialized servers.
Although many domains are touched, each is covered only shallowly. For example, weather lacks historical data, legal lacks case details beyond court opinions, and financial lacks stock prices. There are obvious gaps like no user authentication or data persistence. The tool set feels like a collection of endpoints rather than a cohesive service.