toolkit-mcp-server

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

The annotations already supply readOnlyHint and idempotentHint, and the description adds strong behavioral context beyond that: base64url alphabet substitution, encodeURIComponent/decodeURIComponent semantics, and recoverable-error behavior for malformed decodes. This tells the agent exactly what to expect without contradicting annotations.

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 focused sentences: the first states scope, the second explains operation semantics, and the third adds essential encoding-specific and error behavior. No filler, repetition of schema fields, or unnecessary detail.

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 stateless encode/decode utility with an output schema and fully documented parameters, this is complete: it covers all four encodings, both directions, and the failure mode. Nothing necessary for correct invocation 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?

All three parameters are fully described in the schema (100% coverage), so the baseline is 3. The description adds extra practical meaning for encoding ('base64url uses the URL-safe alphabet', 'url applies encodeURIComponent / decodeURIComponent') and clarifies that value is raw text for encode vs an encoded string for decode, warranting a 4.

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+resource: encode or decode a value across four named encodings, in either direction. This clearly distinguishes it from siblings like hashing, ID generation, QR generation, and IP geolocation without needing to inspect them.

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 explicit operation-level guidance: set operation to "encode" or "decode" depending on the desired direction, with clear expectations for each. It does not name alternative tools or exclusion criteria, so sibling differentiation is implicit by domain rather than explicitly 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 only declare readOnlyHint=true and idempotentHint=false. The description enriches this by clarifying that the result is cryptographically random, that the ids array always contains exactly count values and is never truncated, and that batches for uuid_v7/ulid are monotonic and sorted. These behavioral details go beyond what annotations provide, though it does not mention failure modes or performance characteristics.

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 dense paragraph with zero filler. It front-loads the core purpose, then details types and count, then adds behavioral guarantees and a cross-reference to a related tool. Every sentence earns its place and the structure is logical.

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 only 2 parameters, 100% schema coverage, and a provided output schema, the description is complete. It covers the purpose, usage, parameter semantics, behavioral guarantees, and even a downstream use case. There is nothing an agent needs to know to call it correctly that 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 schema already provides 100% description coverage for both parameters. The description adds value by explaining the semantic difference between uuid_v4, uuid_v7, and ulid (including sortability), the default behavior, and the monotonic ordering within a batch — none of which are in the schema descriptions. It also clarifies the count semantics (exact return size).

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 opens with a specific action ('Mint cryptographically-random identifiers') and a precise resource ('platform CSPRNG'), and immediately distinguishes it from the alternative of model-generated values. It also names the three output formats with their distinct properties, so an agent can clearly tell this tool apart from siblings like toolkit_hash_value or toolkit_generate_qr.

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?

It explicitly states when to use this tool ('IDs that must be unpredictable') and when not ('unlike model-generated values'), and it names a concrete downstream use case (feed ids[0] into toolkit_generate_qr). This leaves no ambiguity about the appropriate context of use.

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?

Beyond the annotations, the description discloses important runtime behavior: exact output forms per format, the returned QR version, the png_base64 pixel formula, the 2048-pixel rejection limit, and the typed raster_too_large error. It also notes that svg has no such size limit, which is valuable behavioral context an agent cannot infer from annotations or schema alone.

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 front-loaded with the core action and then proceeds logically through data, format, error correction, margin, scale, and constraints. Every sentence adds practical information, and the detail is proportionate to the tool's five-parameter complexity 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?

Given five parameters, an output schema, and the presence of siblings, the description covers everything needed to invoke the tool correctly: parameter semantics, format-specific behavior, capacity limits, error types, and interaction effects. 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?

Even though schema description coverage is 100%, the description enriches the parameters substantially by explaining how they interact: errorCorrection trades capacity for damage tolerance, scale is bounded by image size, and dense data may force a lower scale. It also clarifies return-value details like mimeType and byteLength, adding meaning beyond the raw schema entries.

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 opens with a specific verb and resource: 'Encode text or a URL into a QR code.' It then enumerates the three output formats, making it unmistakable what the tool produces and clearly distinguishing it from siblings like toolkit_hash_value, toolkit_encode_value, and toolkit_generate_id.

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 establishes when it is appropriate to use the tool by explaining its purpose and giving concrete examples of valid data, including a generated identifier from toolkit_generate_id. It does not explicitly list when-not-to-use cases or name alternative tools as a routing hint, 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.

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

With readOnlyHint=true and destructiveHint=false already in annotations, the bar is lower, yet the description still adds real context: the provider is called directly (never the target), so it is safe on untrusted input; accuracy is provider-bounded; behavior on private/reserved ranges is stated; proxy/VPN/mobile flags are defined as reliability warnings; and the source field is disclosed. Nothing contradicts the annotations.

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?

All four sentences are substantive and the operation is stated up front in the first sentence, with caveats and security notes after. No filler. Minor redundancy between 'accuracy is best-effort' and 'VPNs, proxies, anycast...' slightly thins the density, but nothing is wasted.

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-param, read-only tool whose output is not schema-described, the description covers: the input types, DNS resolution behavior, the output fields, the meaning of proxy/mobile flags for reliability, and failure modes (private ranges rejected). An agent has everything needed to call it correctly and interpret the result.

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% (the single param is fully defined with three alternates: IPv4, IPv6, hostname). The description adds value beyond the schema by stating that hostnames are DNS-resolved first and that the resolved address is echoed in the response — behavior the schema cannot express. Slightly more caveat detail (e.g., punycode) would push to 5, but coverage is already high.

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 first sentence states a clear verb-resource pair — resolve a public IP or hostname to a set of geographic and network metadata — and enumerates every returned field, so an agent immediately knows what it does and what it returns. It also carves out scope (public only) that distinguishes it in a toolkit whose other tools are QR, hash, and weather related.

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 explains when results are reliable and when they are not (VPNs, proxies, anycast, mobile NAT, reserved ranges), which is implicit guidance to the caller on trusting the output. It does not explicitly contrast with a sibling geolocation alternative, but the sibling set contains no competing tool, so a 4 is appropriate rather than 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the tool's safety profile. The description adds value beyond these: it reveals the timing-safe nature of compare, security caveats for md5/sha1, and the encoding behavior that prevents decode round-trips for binary blobs. It does not contradict annotations or mention any side effects, so the behavioral disclosure is strong.

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 dense but logically structured, starting with the core purpose, then operation, algorithm, encoding, and a canonical use case. Each sentence carries specific information with minimal fluff. It is slightly longer than necessary but remains efficient, and the front-loaded purpose ensures quick comprehension.

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?

With an output schema present, the description need not explain return values. It covers the key behaviors: operation modes, algorithm choices, encoding implications, and the primary use case. Minor gaps exist (e.g., error behavior for missing expected in compare), but these are covered by the schema's required field and are acceptable for an agent to infer.

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% (each param has a description), giving a baseline of 3. The description enhances this with meaningful additions: algorithm security guidance, operation semantics (timing-safe compare), and inputEncoding purpose (hex/base64 for raw binary). It clarifies the relationship between operation, expected, and inputEncoding, going beyond the bare schema definitions.

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 opens with a specific verb+resource pair: 'Generate a cryptographic digest of a value, or verify a value against an expected digest.' It clearly distinguishes between the two operations (generate/compare) and is unambiguous. The sibling tools (id generation, QR, encoding, geolocation) share no overlap, so the tool's purpose stands apart without needing additional differentiation.

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 practical context: 'The canonical use is matching a download against a vendor-published checksum.' It also gives explicit algorithm guidance (sha256/sha512 for security, md5/sha1 only for checksum compatibility) and explains when compare is preferable ('constant-time-check ... timing-safe and avoids manual string equality checks'). While it doesn't name alternative tools, there are no direct competitors among siblings, so the guidance is sufficient for appropriate selection.

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