fetcher sh

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

With no annotations present, the description carries the full behavioral disclosure burden. It discloses that the call is free, that it checks the balance associated with the connection's Authorization header, and implies it is a read-only informational operation. This is good coverage for such a simple tool.

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 short sentences with no redundancy. It front-loads the key value ('Free'), states the action, and then provides a practical usage hint. Every sentence earns its place.

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 utility tool, the description covers what the tool does, its cost implication, the authentication context, and when to call it. Nothing essential is missing.

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 is empty, so there are no parameters to describe. The baseline for zero parameters is 4, and the description adds relevant context by clarifying that the balance is tied to the Authorization header rather than to an explicit parameter.

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 verb ('Show') and resource ('remaining credit balance for the API key'), making the tool's purpose unambiguous. It also distinguishes itself from likely siblings like topup_credits by focusing on balance checking rather than purchasing credits.

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 an explicit timing recommendation: 'Call this before a long run of paid requests.' It does not state when not to use the tool or name alternatives, but the guidance is useful and clear.

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. 'Free' is useful behavioral context, and 'Show the full call signature' suggests a read-only introspection operation rather than an actual endpoint call. Still, it does not explicitly state that no endpoint is executed, no credits are consumed, or that this is purely a documentation/metadata lookup.

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 tight sentence front-loads the most important fact ('Free') and then enumerates the return contents with no wasted words. Every phrase earns its place, and the structure makes the tool's value immediately obvious.

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 tool with no output schema, the description is largely complete: it states cost, input is implied by the path, and it names all output categories. It could be slightly stronger by explicitly connecting to search_endpoints as the way to discover paths, but that gap is minor given the tool's simplicity.

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 schema already documents 'path' with an example. The tool description adds context about what the returned signature contains, but it does not add any new meaning to the path parameter beyond what the schema already provides. 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 uses a specific verb ('Show') with a clear resource ('the full call signature for one endpoint') and enumerates exactly what is included: required and optional parameters, allowed values, price, and response shape. It is immediately distinguishable from siblings like search_endpoints, which searches rather than describes a single endpoint.

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 this tool is for inspecting a specific endpoint once its path is known, and 'Free' signals it is safe for discovery. However, it never explicitly says 'if you don't know the path, use search_endpoints first' or mentions when not to use it, so the routing guidance is only implied rather than stated.

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?

Annotations are absent, so the description carries the full burden — and it delivers: it front-loads that the tool is paid, specifies pricing per call in USDC on three chains, and discloses both payment paths (x402 or Bearer bby_live_... header for prepaid credits). For a tool with zero annotation coverage, this is strong behavioral disclosure. It loses a point for not addressing failure behavior, rate limits, or what happens on invalid payment, but the cost/auth essentials are unusually well covered.

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 short sentences, each earning its place: purpose and paid status are front-loaded, invocation follows, payment mechanics next, and routing guidance closes. There is zero filler and the most decision-relevant information (cost, generic scope) appears first.

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 generic proxy to arbitrary endpoints, response format is inherently endpoint-specific, so the absence of return-value documentation is excusable. The description covers cost, invocation, and parameter discovery via describe_endpoint. Minor gaps: it never states that the raw endpoint response is returned, nor error handling for failed payments or bad paths — but for a tool this open-ended, the coverage is solid.

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%: both path and params already have meaningful schema descriptions with examples. The description's 'path and query parameters together in params' note slightly reinforces the schema's statement but adds little new semantic information. Baseline 3 applies because the schema does the heavy lifting.

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 states a specific verb and resource: 'Fetch live data from any fetcher.sh endpoint.' This clearly identifies it as a generic dispatch/proxy tool for arbitrary endpoints, which distinguishes it from its siblings (search_endpoints finds endpoints, describe_endpoint describes them, check_balance and topup_credits handle billing). The scope and role are unmistakable.

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 routing guidance: 'Call describe_endpoint first if unsure about parameters' and 'For a named tool per endpoint, use [service].fetcher.sh/mcp.' Together with the schema's reference to search_endpoints as the path source, an agent knows exactly which sibling to use when. The when-not guidance for fetch_data (use a named tool) is stated directly.

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 supplied, the description carries the transparency burden. It discloses that the search is free, that it is a search operation (therefore read-only in nature), and exactly what it returns: paths, descriptions, and per-call prices. It does not discuss pagination or auth, but those are not critical for this kind of catalog lookup.

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?

Three short sentences with no filler. The long service list is justified because it defines the catalog scope, and the key facts ('Free', what it returns, 'Start here') are front-loaded or clearly placed.

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, optional-parameter discovery tool with no output schema, the description says enough: what it operates on, how to scope a search, what will be returned, and the cost of the search call. It could optionally mention behavior with no query or the result-set structure, but that is a minor gap.

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%, so both parameters are already documented with examples. The phrase 'by keyword and/or service' aligns with query and service but adds no new format, defaults, or validation details; the schema already carries the load.

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 action ('Search'), a concrete resource ('fetcher.sh's web-data endpoints'), and the two search dimensions (keyword and/or service). It also states what it returns (paths, descriptions, per-call prices), which distinguishes this catalog-discovery tool from sibling tools that fetch actual data.

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?

'Start here' provides an implied usage context: this is the discovery entry point for the endpoint catalog. However, it does not explicitly say when to use a service-specific sibling such as twitter_search or describe_endpoint, nor does it tell the agent what to do after finding an endpoint.

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 of behavioral disclosure. It clearly explains the payment requirement, the recharge versus new-key behavior, the one-time key return, and the critical caveat that the key cannot be recovered. This is rich, honest behavioral context.

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 compact yet information-dense, with every sentence contributing essential details. The key caveat about key recovery is front-loaded near the end, and there is no filler or repetition.

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 tool with no output schema and no annotations, the description provides enough context to invoke it correctly: payment amount, minimum, auth modes, and outcome. It does not describe error cases or the exact response format beyond key return, but the critical operational details are present.

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%, so the baseline is 3. The description adds meaningful context beyond the schema by explaining how the amount ties to prepaid credits, how the Authorization header changes the effect of the call, and that a new key is returned only once and must be stored as a secret. This enhances the parameter understanding.

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 states a clear action ('Buy prepaid credits with x402') and a specific resource, making the tool's purpose immediately identifiable. It also explains the benefit ('later calls skip the per-call payment round trip'), which helps distinguish it from the other listed 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?

The description gives explicit instructions for two use cases: with an Authorization header it recharges the key, and without one it mints a new API key. It does not explicitly compare against sibling tools, but the usage 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.