devutils

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

No annotations, so the description carries the full burden. It usefully discloses the output encoding (UTF-8) and the failure mode (errors on invalid base64), which are real behavioral traits. It omits whitespace/padding tolerance, URL-safe variant support, and expected output on empty input.

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 short sentences with zero waste; the operation is front-loaded and the error behavior follows. 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 one-param, no-output-schema utility, the description covers purpose, output encoding, and error behavior — enough to call it correctly. Input-format edge cases are the only meaningful omission.

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 0%, so the schema only names the param 'text' with no description. The description implies it holds base64-encoded input but says nothing about accepted format variants (padding, URL-safe alphabet, embedded whitespace), so it only partially compensates.

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: decode base64 to text. The counterpart sibling base64_encode makes the direction unambiguous. No explicit sibling routing, but the operation is fully distinguishable from all other siblings.

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?

Usage is implied by the name and description — use it when you have base64 to convert to text. No explicit when-to-use conditions, prerequisites, or named alternatives (e.g. for URL-safe or binary payloads).

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 burden. It does disclose the UTF-8 input encoding assumption, which is real behavioral context for a pure transform, but it says nothing about the return form (Base64 string, padding behavior) or error 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?

A single short sentence, front-loaded with the verb and resource, with the UTF-8 qualifier appended efficiently. 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 trivial, pure one-parameter transform with no output schema, the definition covers what the tool does and the input encoding. Only minor gaps remain: the returned Base64 string format and handling of invalid input are unstated.

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 0% and the single parameter is undocumented in the schema, but the description does clarify that 'text' is UTF-8 input, adding some meaning. With only one self-explanatory required parameter, this is close to adequate but not fully compensating for the coverage gap.

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 combination ("Base64-encode a text") that is unambiguous and directly distinguishes it from the sibling base64_decode. It does not, however, explicitly discuss other siblings like hash_text, so it stops short of full 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?

Usage is strongly implied by the name and description - encode text to Base64 - but no explicit when-to-use or when-not-to-use guidance is given, nor are alternatives referenced. Adequate as an obvious utility, but nothing steers an agent between it and base64_decode/hash_text.

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, so the description carries the burden. It does disclose the output shape (array of row objects) and the header-row precondition, which is real behavioral information. It is silent on edge behavior an agent would want: handling of ragged rows, quoting/embedded commas, missing header, and whether values are coerced to numbers or kept as strings.

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 with the input format, its precondition, and the return shape all front-loaded. Nothing is wasted and nothing needs to be re-read.

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?

There is no output schema, and the description does supply the return shape (array of row objects), which covers the main gap. It falls short only on malformed-input and type-coercion behavior, which for a one-parameter pure transform is a minor omission rather than a blocking one.

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% and the single parameter 'text' is already documented as a CSV document. The phrase 'with header row' adds a genuine constraint on that input beyond the schema, but that is the only added meaning, so the baseline 3 holds with slight credit.

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 (convert), a specific input (CSV with header row) and a specific output shape (array of row objects). No sibling in the list does CSV parsing, so it is unambiguously distinguishable from json_format, json_validate, etc.

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?

Usage is implied by the input constraint (CSV must have a header row), but there is no explicit when-to-use or when-not-to-use guidance and no mention of alternatives. For a single-purpose utility with no true sibling overlap, implicit usage is adequate but not instructive.

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 behavioral burden, yet it discloses nothing beyond the algorithm list — not the output shape (single digest vs. a map of four), not whether input is treated as UTF-8, and not error behavior. For a pure-function hashing tool this is a modest but real gap.

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 short sentence, front-loaded with the algorithm list. It is a fragment without a verb, but nothing is wasted and there is 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?

For a one-parameter tool with no output schema, the key missing piece is what the caller gets back — one digest or four — plus input encoding assumptions. The description is adequate to identify the tool but not fully sufficient to predict its 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% and the single 'text to hash' parameter is fully documented in the schema, so the baseline is 3. The description adds only the algorithm vocabulary and no encoding or size hints beyond what the schema already supplies.

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?

Names the resource precisely (hex digests of a text) and enumerates the four supported algorithms, which clearly distinguishes it from siblings like base64_encode or uuid. However, it never states whether all four digests are returned together or whether the algorithm is somehow selected (the schema has only one parameter), leaving a small ambiguity about the operation's shape.

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?

There is no guidance on when to use this versus alternatives, nor any note on constraints (e.g., input encoding, empty-string behavior). The sibling set is different enough that an agent can infer the purpose, but the description contributes nothing toward that routing decision.

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 burden, but it is a deterministic pure transform with low risk. It states the output style (2-space indent) yet omits error behavior on malformed input and whether the indent parameter overrides the stated default.

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?

A single front-loaded sentence with zero padding. Appropriately sized for a trivial utility, though it leaves no room for the constraints an agent would benefit from.

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 two-parameter, no-annotation, no-output-schema utility the core contract is conveyed. Still missing the failure mode for invalid JSON and any note on return value, which matter for an agent deciding whether to chain json_validate first.

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 50%: the indent parameter is documented ('default 2, max 10') while text is bare. The description reinforces the default indent value but adds no syntax, size, or validity constraints for text.

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?

Specific verb (pretty-print) plus resource (JSON) and even the output shape (2-space indent). An agent can distinguish it from json_minify and json_validate by name alone, though the description never explicitly contrasts 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?

No guidance on when to use this versus json_validate or json_minify, and no statement of what happens if the input is not valid JSON. The agent must infer that this is the right tool for reformatting.

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 behavioral burden. It discloses the transformation (whitespace stripping) but says nothing about error behavior on invalid JSON, the return format, or whether the input is mutated or copied. For a pure function this is a modest but real gap.

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 short sentence, front-loaded with the core action, with zero wasted words. Perfectly sized for a trivial transformer.

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 one-parameter pure transformation with no output schema, the description covers the essence but omits edge-case behavior (invalid JSON handling) and return semantics. Adequate but with clear gaps.

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 0% and the single parameter is named 'text' without a schema description. The description implies this parameter is the JSON to minify, which adds meaning beyond the bare name, but it does not specify format expectations or constraints.

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 ('Minify JSON') and parenthetically clarifies the operation ('strip whitespace'). It is clearly distinguishable from siblings like json_format and json_validate, though it does not explicitly name 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?

There is no guidance on when to use this tool versus alternatives such as json_format (the inverse operation) or json_validate. The description only states what it does, not when to choose it.

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 usefully discloses the error-path return shape (line/column and message), but says nothing about the success-path response, whether it is pure/read-only, or whether validation is strict or lenient (e.g. trailing content).

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?

A single compact sentence with the core action front-loaded and the error behavior appended where it is most useful. 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?

For a one-parameter, no-annotation, no-output-schema tool this covers the essentials. The remaining gap is the success return value (boolean? parsed object? empty?), which the agent would need to know to consume 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?

Only one parameter, and schema_coverage is 100% with the schema already describing 'text' as 'JSON document to validate'. The description adds nothing beyond that, so the baseline 3 applies.

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 ('Validate a JSON string'), which is immediately distinguishable from siblings like json_format and json_minify. It stops short of explicitly naming those siblings as alternatives, so differentiation is inferred from the verb rather than stated.

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?

Usage is implied by the word 'validate' against a syntax-checking sibling set, but the description never says when to pick this over json_format or json_minify, nor that it performs no reformatting. An agent must infer the routing.

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 and does disclose the single most important behavioral trait: it does not verify signatures. It also states the returned fields (header, payload, expiry). It omits what happens on malformed or non-JWT input, which would be the remaining gap.

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?

A single front-loaded sentence with the operation first and the safety caveat immediately after. No filler, no restatement of the title.

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 one-parameter read tool with no output schema, the description covers the return shape (header + payload + expiry status) and the verification caveat. Error behavior on invalid tokens is the one missing piece an agent might want.

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?

Only one parameter at 100% schema coverage, and the schema already documents it as 'the JWT (3 dot-separated parts)'. The description adds no format or syntax detail beyond that, so this sits at the schema-backed baseline.

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?

Specific verb 'Decode' tied to a specific resource 'JWT header + payload', plus a stated scope limit (no signature verification) and an output facet (expiry status). It is clearly distinct from siblings like base64_decode or json_format, though it never names 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?

'No signature verification' implicitly signals the trust/inspection use case, but there is no explicit when-to-use statement, no guidance on when to prefer base64_decode or a verifying alternative, and no prerequisite or error-case notes.

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 does reveal the return payload components (ISO-8601, unix, relative delta), but says nothing about precedence when both params are set, invalid-epoch handling, or that the operation is a side-effect-free read — all of which an agent must guess at for a no-annotation 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?

A single sentence with the primary behavior (current time) front-loaded and the optional conversion mode trailing. Zero 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?

For a two-optional-param utility with no output schema, the description covers both modes and the shape of the returned values, which is enough to call it correctly. The only real gap is the unspecified behavior when both `iso` and `unix` are supplied.

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% and both optional params are documented in the schema, so the baseline is 3. The description only adds the notion that supplying a value switches the tool into conversion mode and yields a relative delta; it adds no format or precedence 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 names a specific resource and two behaviors: returning the current time in ISO-8601 and unix, and converting a supplied timestamp into a relative delta. This is unambiguous and no sibling in the list (base64, hash, json, jwt, uuid) overlaps, so no explicit differentiation is needed.

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 word 'Optionally' implies the params are used for conversion mode versus the no-arg clock mode, which is a usable hint. However, it never states what happens when both `iso` and `unix` are supplied, nor does it spell out 'call with no arguments to get the current time' as an explicit condition.

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 usefully discloses that output is random UUIDv4 (not v1/v7) and that it is a pure generation operation, but it says nothing about return shape (single value vs. array when n>1) or whether randomness is cryptographically secure.

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?

A single front-loaded sentence with zero waste. Everything present is necessary and nothing extraneous is included.

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 one-parameter, no-annotation utility, the description covers what is generated and the count range. The one remaining gap is the return shape when n>1 (single string vs. list), which matters for an agent consuming 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 description coverage is 100% — the 'n' parameter is fully documented in the schema with default and max. The '(1-100)' in the description reinforces the range but adds no new semantics, so baseline 3 applies.

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: 'Generate random UUIDv4s' with a generation range. It's clearly distinct from siblings like hash_text or now, but the description never names or contrasts those tools, so it earns a 4 rather than a 5.

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?

Usage is implied by the operation itself: generate UUIDs when you need unique identifiers. There is no explicit when-to-use/when-not framing or mention of alternatives, which is acceptable but leaves inference to the agent.

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