agent-tool-finder

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

No annotations are provided, so the description carries the transparency burden. It discloses the 30-day window and that the tool is 'Free,' but does not describe the output format or authentication requirements. The read-only nature is implied by 'Get' and the stats context but not explicitly stated.

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, front-loaded with the main verb and purpose. The second sentence provides a use case and cost note, both valuable. No wasted words.

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 zero-parameter, no-output-schema tool, the description covers the key information: what is measured, the time window, and a use case. It is complete for an AI agent to decide when to invoke it.

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 tool has zero parameters, so schema coverage is effectively 100%. The description adds no parameter-specific semantics, but none are needed. Baseline 4 for zero parameters 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 the specific verb 'Get' and identifies the resource as 'the agent tool market' with concrete metrics (paid x402 endpoints, MCP servers, paying users, spend). This clearly distinguishes from the sibling find_agent_tools, which searches for individual tools.

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?

Provides a clear use case: 'deciding whether a capability is well supplied before you build it yourself.' It does not explicitly mention alternatives or when not to use, but the context is clear and actionable.

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?

No annotations are provided, so the description must carry the burden of behavioral disclosure. It states the tool 'Searches 35,000+ agent-callable tools', is 'Free to use', and 'Returns what each tool does, how to call or install it, and what it costs'. However, it does not mention potential limitations, rate limits, or that it only searches (does not execute) the tools, leaving some behavioral ambiguity.

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, front-loaded paragraph that opens with the core purpose and then provides supporting details. It is slightly long due to enumerating many use cases, but every sentence contributes useful information without fluff.

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?

Given there is no output schema, the description appropriately explains what the tool returns (what each tool does, how to call/install, costs). It covers the main use cases, scope, and cost. It does not explicitly address the sibling tool or any limitations, but for a search tool of this complexity it is largely 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 100%, so the baseline is 3. The description adds context for the 'need' parameter with examples like 'historical lithium spodumene prices' but does not explain the meaning of each parameter in prose. It provides no additional semantic detail 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's purpose with a specific verb ('Find') and resource ('API, data source, or MCP server'). It also differentiates from the sibling tool agent_market_stats by focusing on discovery of external tools rather than market statistics.

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 gives explicit, concrete guidance on when to use the tool: 'Use it whenever you need outside data or a capability you lack' followed by numerous examples. It does not explicitly mention alternatives or exclusions (e.g., using agent_market_stats for stats), so it misses the full 'when-not-to' guidance.

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 behavioral burden well: it discloses that clink reads requests same day, buildable asks ship as pay-per-call x402 endpoints usually within a week, and it returns a request id and status URL. It also explains the notify option and the decline path.

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?

Four sentences, front-loaded with purpose and usage, then process and return details. Every sentence adds information with no filler.

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?

Complete for a request-submission tool: it covers when to use it, what happens after submission, expected turnaround, return values, and notification. No output schema exists, but the return shape is described sufficiently.

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 100%, so the input schema already documents all three parameters. The description only reiterates the notify parameter and adds no extra meaning for want or budget_usd, making the baseline 3 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?

States a specific verb and resource: ask clink's shop to BUILD a tool or data source that nobody sells yet. It explicitly differentiates from find_agent_tools by saying to use it right after that sibling comes back unsatisfied.

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?

Gives a precise condition: use this right after find_agent_tools comes back unsatisfied. It names the alternative and leaves no ambiguity about when this tool is appropriate.

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