agent-context-api

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It covers important behavioral context: the lookup is read-only, returns multiple intelligence categories, uses daily-refreshed lists, and produces an explainable risk score. This gives the agent a solid mental model, though it could mention limitations like missing data or unrestricted IP handling.

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, tight sentence that packs useful detail without a wasted word. It front-loads the core action, then efficiently enumerates the value-add results. This is appropriately sized for the tool's simplicity.

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 single-parameter lookup tool with no output schema, the description supplies enough context about what it returns and why the data is trustworthy. It does not spell out error behavior or the exact output shape, but for a simple non-destructive lookup the given coverage is largely sufficient.

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 input schema has full description coverage for the single 'ip' parameter, so the schema already documents that IPv4/IPv6 addresses are accepted. The description adds no new parameter-level detail beyond restating that it supports both IP formats; the baseline 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 uses a specific action verb ('Look up') and a clear resource ('IPv4/IPv6 address'), then enumerates exactly what the tool returns: country, ASN, hosting/ISP classification, VPN/proxy/Tor/datacenter flags, and risk score. This is easily distinguishable from sibling tools named preflight_context and read_page_preview, which are clearly about other concerns.

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 the use case — when you need IP enrichment or risk intelligence for an address — but it does not explicitly state when to prefer this tool over alternatives or when not to use it. No exclusions or comparisons are provided, so the guidance is implicit rather than direct.

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

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

With no annotations, the description carries the transparency burden. It discloses that redaction happens locally and that there is a size-dependent API requirement. However, it does not describe the output format, whether the input is modified, or what happens when the budget is exceeded, leaving gaps.

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 two sentences: the first lists the core functions, the second a key constraint. Every word earns its place, and the most important information 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 explains the tool's main operations and a size limitation, but without an output schema, it fails to clarify what is returned. It also omits edge-case behavior (e.g., empty input, budget enforcement mechanics). For a tool of this complexity, more detail is needed to be fully 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 coverage is 100%, but the description adds valuable nuance: 'model-aware budget' explains how token_budget interacts with the model parameter, and 'locally' clarifies that redaction is client-side. These additions go beyond the schema's basic field descriptions, providing meaningful context.

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 three specific functions: counting tokens, applying a model-aware budget, and redacting credentials. This is a specific verb+resource definition that matches the tool name and leaves no ambiguity about its purpose.

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 clearly implies when to use the tool (whenever token counting, budgeting, or redaction is needed) and mentions a critical usage constraint (12,000-character threshold requires paid API). However, it does not explicitly discuss alternatives or exclusions, which would push it to a 5.

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

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

With no annotations provided, the description carries the full burden. It discloses key behaviors: returns Markdown, truncates to 2,000 characters, and includes metadata (URL, status, byte counts). It also states the cost implication for full access. While it doesn't explicitly mention read-only semantics or error handling, the fetch nature and the preview limit cover the essential behavior.

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 sentences with no fluff. The first sentence front-loads the core action and output, the second provides pricing and alternatives. Every word adds value and the structure is clear.

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 fetch tool with no output schema, the description gives enough: it tells what the tool returns and the limitation. It also mentions the alternative for full access. Minor missing details like error handling or redirects are not critical for a preview tool, and the schema covers parameter constraints. The description is adequate for an agent to call it correctly.

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 input schema already describes both parameters with 100% coverage. The description does not add additional parameter-specific guidance beyond what's in the schema; the mention of 'first 2,000 characters' is about output behavior, not parameter semantics. According to the rubric, when coverage is high, baseline 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 precisely states the action ('Fetch') and the resource ('public web page'), and enumerates the exact output: Markdown preview, first 2,000 characters, final URL, status, and byte counts. This clearly differentiates it from the sibling 'preflight_context' by framing it as a preview tool.

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?

Explicitly explains when to use this tool: 'Free local preview; the full page requires the paid HTTP API (x402, $0.01/call).' This directly guides the agent to choose the preview tool for quick checks and points to the alternative for full content. The scope is also limited to 'public' pages, setting boundaries.

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