MCPFax Feed Reader

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

There are no annotations to provide behavioral hints, and the description lacks any details about side effects, permissions, read-only nature, or whether data is modified. The only extra is a cost note, which is not a behavioral trait. This is insufficient for an agent to understand the tool's impact.

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 rambling sentence that mixes unrelated info ('FREE, no payment') with the main purpose and ends in an unclear phrase. It is not well-structured or concise, and important elements are buried or unclear.

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 appears simple but lacks essential context: no output format, no explanation of how it differs from sibling tools, and the cost hint is not elaborated. An agent would struggle to know what to expect or when to use it, making the description incomplete for decision-making.

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 fully defines the 'days' parameter with a clear description, default, and max value (coverage 100%). The tool description does not add further semantic meaning beyond the schema, so the baseline score of 3 applies, with no additional insights provided.

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 the tool provides an aggregate of agent requests, sorted by frequency, and the title reinforces this. However, the phrasing is awkward and includes a garbled clause ('with the categories nothing available yet serves') that detracts from clarity. It does not clearly distinguish from sibling tools, but the core action is discernible.

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 only mentions 'FREE, no payment,' which hints at a cost benefit but does not explicitly state when to use this tool over alternatives like discover_feeds or read_feed. There is no guidance on conditions or scenarios for use, leaving the agent to infer appropriateness.

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 explains the return shape, the fallback behavior of suggesting conventional locations marked as guesses that may 404, and discloses the cost of $0.005 USDC per call via x402 on Base. This is unusually transparent.

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 and front-loaded, leading with the core behavior, then the use case, fallback behavior, and cost. Every sentence earns its place and there is no redundant or filler wording.

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, and the description covers the return value, the use case, the failure/fallback case, and cost. An agent has enough information to invoke the tool correctly and interpret results.

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 the single url parameter fully with an example and explanation, so schema coverage is 100%. The description adds only the phrase 'normal URL,' which is mildly clarifying but does not substantially go 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 states a specific verb and resource: given a site's normal URL, return the feeds it declares in its HTML head, each with title and type. This clearly distinguishes the tool from siblings like read_feed, which likely fetch and parse feed content rather than discovering feed locations.

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 explicitly states when to use the tool: when you know a site publishes updates but not where its feed lives. It does not explicitly name alternatives or state when not to use it, but the use case is clear enough for an agent to select it appropriately.

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 carries the full burden. It discloses the cost ($0.005 USDC per call via x402 on Base) and normalization behavior, which is useful. However, it does not mention error handling, rate limits, or what happens on invalid URLs. For a read tool with no annotations, this is adequate but not comprehensive.

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—three sentences covering the main function, normalization, polling hint, and cost. It is front-loaded with the core action and avoids fluff. Slightly long due to the cost mention, but that information is valuable and 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?

Despite no output schema, the description explicitly lists the returned fields (title, link, ISO-8601 date, author, summary, categories, feed title, last-build time), which is critical for an agent to know what to expect. It also explains normalization and cost. It doesn't cover errors or edge cases, but for a simple fetch tool this is fairly 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% (all three parameters have descriptions), so the baseline is 3. The description adds minimal new information about parameters—it repeats the 'since' usage but doesn't clarify syntax or edge cases beyond what the schema already provides. It does not compensate for any gaps because there are none.

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 ('Fetch') and resource ('any RSS, RSS/RDF or Atom feed') and clearly distinguishes the tool's purpose: returning a normalized, consistent shape across feed dialects. This is unambiguous and immediately tells an agent what the tool does.

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 for polling via the 'since' parameter ('the cheap way to poll for what changed'), giving contextual guidance. However, it does not explicitly name alternatives like discover_feeds or demand_report, nor does it state when not to use this tool. The guidance is implied rather than explicit.

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 full burden of behavioral disclosure. It explicitly discloses that the service is free, that requests are catalogued, that nothing identifying is stored, and that only the words of the request are kept. This is unusually transparent for a request tool and covers privacy and data-handling behavior beyond the obvious purpose.

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 sentence that opens with the key free-of-cost detail, then states the purpose and outcome, and closes with privacy guarantees. Every clause contributes meaning, with no fluff. It is concise and well-structured.

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 tells the agent exactly what to expect: whether the service supplies the data and the endpoint if so. It also covers side effects (cataloguing) and privacy. Nothing essential is missing for an agent to decide to call this tool and know what will happen.

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 already describes the only parameter 'need' as 'What you are looking for' with an example. The description adds value by clarifying the format: 'Describe in your own words' and the scope 'anything, not just feeds'. This goes beyond the schema's bare definition, so a score above the baseline 3 is warranted.

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 ('request'), the resource ('data'), and the outcome ('get back whether we operate a service that supplies it, with the MCP endpoint if so'). It distinguishes itself from siblings by emphasizing 'anything, not just feeds', which signals it is a broad inquiry tool rather than a feed-specific discovery or read operation. The purpose is unambiguous.

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 when to use it: when you want to ask about data availability in free-form. The phrase 'not just feeds' subtly contrasts with feed-specific siblings (discover_feeds), and the context 'trying to buy' suggests a pre-purchase inquiry. However, it does not explicitly state when not to use it or name alternatives, so it stops short of a 5.

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