Susurration puzzles

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

With no annotations, the description carries the full burden, and it does disclose the key behavior that the reply only says correct or not correct and never reveals the answer, plus that method is "never published". It is silent on resubmission, overwriting, rate limits and what happens on a malformed or duplicate submission, which matters for a submit tool with zero annotation coverage.

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, front-loaded with the action and the most decision-relevant fact (the reply never reveals the right answer), then the optional fields. Nothing is padded.

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 submit-style tool with a deeply nested signature object, no annotations and no output schema, the description correctly explains the response shape and the optionality of method/name/signature. It leaves open submission lifecycle questions (repeat answers, whether an answer locks, failure modes) that an agent would want before calling.

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 schema already documents id, answer, confidence, method, name and signature, including the exact signing preimage. The description only restates which fields are optional and adds a "see /about" pointer, so it adds little meaning 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?

"Answer one of today's puzzles" gives a specific verb and a scoped resource, and the confidence clause signals this is a scored submission rather than a lookup. It is clearly distinct from puzzle_get, puzzles_today and leaderboard, though it never names a sibling explicitly.

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 "today's puzzles" and the required puzzle id, so an agent can infer it needs an id from puzzles_today first. There is no explicit statement of when to submit versus fetch (probe/puzzle_get) or whether multiple or repeat submissions are allowed.

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, and it does useful work by disclosing the scoring rule (only the FIRST correct answer per key per puzzle counts) and the UTC Monday week boundary — non-obvious logic an agent could not get from the schema. It leaves gaps that matter for interpreting output: whether all keys are listed or only a top slice, whether the result is ordered, and what an inactive week returns. These are inference-level gaps for a simple read tool, not contradictions.

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, both load-bearing: the first defines the payload and its aggregation rule, the second defines the time window. The resource and cadence are front-loaded, and there is no filler, hedging, or restated tool name.

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-optional-parameter read tool with no annotations and no output schema, the definition covers what the data means and how weeks are computed, which is the hard part. It omits result ordering and any cap on the number of keys returned, so an agent cannot fully predict the shape of a response — the only remaining gap for a tool this simple.

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 baseline would be 3, but the description adds meaning the schema does not contain: that weeks are anchored to Monday in UTC, which tells the agent how a mid-week date is bucketed. The schema already covers the YYYY-MM-DD format and the 'any day of the week' default, so the description is not just restating it. It stops short of explaining how the boundary interacts with the default value.

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 clause names the resource (leaderboard) and its cadence (weekly), and the colon-introduced clause states exactly what is aggregated: points per signing key for the first correct answer to each puzzle. It is specific rather than tautological. It does not explicitly say 'returns/retrieves', and there is no sibling differentiation, but no sibling (answer_submit, probe, puzzle_data, puzzle_get, puzzles_today) overlaps in purpose, so confusion risk is low.

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 explicit when-to-use, when-not-to-use, or alternative-tool guidance; usage is only implied by the tool's name and the fact that it is the sole leaderboard endpoint. The week-boundary and default-week semantics in the schema make invocation predictable, which partly compensates. Nothing misleading, but the agent must infer the trigger 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 of behavioral disclosure. It says one probe returns f(x), but it does not state whether probes are limited, whether calls have side effects, what output format to expect, or what errors may occur when x is outside the domain.

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 definition is a single front-loaded sentence with no extraneous steps. The phrase "black box of a black-box puzzle" is slightly redundant, but the description remains efficient.

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 tool with full schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it could do more to explain expected return values and probe limitations.

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 in the schema. The description reinforces that x must be a whole number in the domain stated in the question, but it does not add further meaning for id or clarify domain boundaries 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 action: evaluating a black-box function f(x) for a given puzzle input. It clearly distinguishes the operation from puzzle metadata and answer submission, though it does not explicitly name sibling alternatives.

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: this tool is for probing the puzzle function with a whole number in the stated domain. There is no explicit when-to-use versus when-to-use-alternatives guidance, such as when to call probe instead of puzzle_get or puzzle_data.

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 gives no information about read-only status, permissions, response format, dataset size, or side effects. The phrase 'The dataset of a computing puzzle' only vaguely implies retrieval and discloses no operational traits.

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?

It is a single short sentence with no wasteful clauses, so it is concise and front-loaded. However, the brevity reflects under-specification rather than crisp communication.

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 has no output schema and no annotations, and the description does not explain what the dataset contains, how it is returned, or how it relates to sibling puzzle tools. It is incomplete for a data-retrieval endpoint even though the single parameter is fully documented.

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 the single id parameter includes an example value, so the schema already documents the only input. The description adds no meaning beyond what the schema provides, making the baseline score of 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?

The description is a noun phrase that names a resource ('dataset') but never states an action, so the agent cannot tell whether this retrieves, lists, or computes the dataset. It also fails to distinguish this tool from siblings such as puzzle_get and puzzles_today.

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 when-to-use guidance and no mention of alternatives like puzzle_get. The agent must guess whether this is the right tool for fetching puzzle data versus retrieving metadata or submitting an answer.

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. It does disclose one genuinely useful behavioral trait beyond structured fields: results vary by date, and puzzles from earlier days include their answer. It omits not-found/error behavior and any permission or rate-limit context, leaving meaningful gaps for a zero-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?

Two short sentences, front-loaded with the core action, and no redundant or filler wording. Every clause contributes information.

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 annotations and no output schema, the description covers what is needed to call it and flags the notable answer-inclusion behavior. It could be stronger by stating the not-found behavior and confirming it is a read-only lookup.

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 the schema already provides the id type, max length, required flag, and a concrete example value. The description adds no format or semantics beyond "by id", 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?

"One puzzle by id" gives a specific retrieval verb and resource, and the singular framing implicitly separates it from the list-style sibling puzzles_today. It does not explicitly address puzzle_data, which sounds like it could also return a single puzzle's contents, so an agent cannot fully disambiguate the two from this text alone.

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 only implied: fetch a single puzzle when you already have its id. There is no explicit "use this instead of X" statement naming puzzles_today or puzzle_data, and no guidance about calling answer_submit afterward. The note about earlier-day answers hints at a workflow but never states one.

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 it does disclose a real behavioral trait beyond structure: puzzles refresh at 00:00 UTC. It does not state whether the call is side-effect free, whether results are stable within the day, or what happens at a day boundary / with no puzzles — gaps for an unannotated tool, though the tool is simple.

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 filler; the refresh cadence sits inline in parentheses right where it matters. It is telegraphic to the point of being slightly clipped ('id, kind, points, question and answer format'), but every clause 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?

No output schema exists, so the description must convey the return shape, and it does by listing the five fields plus the update cadence. For a zero-parameter read tool this is close to complete; only failure/empty-day behavior and an explicit read-only statement are 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 tool takes zero parameters, so the baseline of 4 applies. The description adds nothing parameter-related because there is nothing to explain, and it correctly implies no inputs are needed.

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 scope ('Today's three puzzles') and enumerates the returned fields (id, kind, points, question and answer format). It is clearly distinguishable from a generic puzzle lookup, though it never explicitly names siblings like puzzle_data or puzzle_get, so differentiation is left to implication.

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?

Use is only implied by the word 'Today's' — an agent can infer this is the fetch for the current day's puzzles, but there is no explicit when-to-use versus puzzle_get/puzzle_data, and no prerequisites or edge conditions are stated.

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