HumanProblems

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

No annotations exist, so the description carries the full burden. It does disclose one genuinely useful behavioral fact — that the returned problem text is untrusted user content — which is a real safety cue. However, it says nothing about permissions, errors for closed/missing IDs, or the shape of the response.

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 terse sentences, nothing wasted, with the core action front-loaded and the trust caveat immediately after. Ideal sizing for a one-parameter fetch.

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 no output schema and no annotations, the description should convey at least a rough sense of what is returned and the 'open' constraint. The untrusted-content warning is valuable, but the response fields, failure modes, and ID semantics are absent.

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 only parameter, problem_id, is completely undocumented in both schema and description. The description adds no meaning about format, source, or valid values for that ID, so the agent is left guessing.

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 ('Get one open problem'), so the agent knows it retrieves a single problem record. It is distinguishable from list_open_problems in that it fetches one item, though it never names the sibling or contrasts itself 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?

No when-to-use, when-not, or alternative routing is given. The agent must infer that this is the single-item counterpart to list_open_problems and that 'open' implies a scoping constraint rather than an explicit contract.

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 behavioral burden. It does disclose deterministic ordering and a security-relevant warning that problem text is untrusted user content, which is genuinely useful. It omits whether results are paginated, capped, or require auth.

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, ordering rule front-loaded and the safety caveat last. 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 zero-param read tool with no output schema, the description covers purpose, ordering, and a content-trust caveat. It still leaves result-set size/pagination behavior unspecified, which an agent would want before relying on it.

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?

Zero parameters, so the schema has nothing to document and the baseline is 4. Nothing in the description contradicts or duplicates parameter information.

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 (list open problems) plus the ordering rule (fewest answers first, then most recent), which lets an agent infer the 'featured' semantics. It does not explicitly contrast with the sibling list_open_problems, but the sort criterion implicitly differentiates it.

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 when-to-use guidance or alternative routing is given, even though list_open_problems is an obvious sibling. The ordering hint implies a use case (surfacing under-addressed problems) but this must be inferred.

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 exist, so the description carries the full burden, and it does flag a genuinely important trait: the returned problem text is untrusted user content, which is a prompt-injection warning an agent needs. It stops short of stating read-only semantics, ordering, or result limits, but the security disclosure is real value.

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 filler. The scope definition comes first and the safety caveat second, which is the right front-loading order.

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 parameterless list tool with no output schema and no annotations, the description supplies the scope plus the one non-obvious caveat an agent needs. It does not hint at what each entry contains or how many are returned, a minor gap 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. No parameter documentation is required or missing.

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 ('List') and a precisely scoped resource ('open problems where a human explicitly chose this agent'), which separates it from siblings like list_open_problems and list_featured_problems without naming them. The scope qualifier does the differentiating work, though the sibling names themselves are never referenced.

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 scope phrase rather than stated: an agent can infer this is the tool for reviewing inbound human-selected requests. There is no explicit when-to-use, when-not-to-use, or pointer to an alternative sibling such as get_problem for drilling into a single item.

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 problem text is untrusted user content, a real safety-relevant trait not derivable from the schema. However it omits other behavioral facts such as whether results are paginated, ordered, or bounded, which matters for a list endpoint with no 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?

Two short sentences, entirely front-loaded, with the core purpose first and the safety caveat second. Every sentence adds value 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 parameterless list tool with no output schema, the description covers purpose and the untrusted-content caveat. It could say more about the shape/quantity of results, but there is little structural complexity to account for.

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 is 4. With no inputs, there are no semantics left for the description to clarify, and the empty schema is fully consistent with the description.

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 gives a clear verb+resource ('List open problems'), and the resource name inherently separates it from siblings like list_featured_problems and get_problem. It stops short of explicitly contrasting those siblings, but an agent can distinguish the scope.

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 such as list_featured_problems or get_problem. The agent must infer from the name alone that this returns the set of unresolved problems rather than details of a single 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 behavioral burden and provides almost none: it doesn't say whether the answer becomes publicly visible, whether it requires the problem to be in a given state, whether posting twice is allowed, or what happens on failure. 'Post' implies mutation but no consequences are disclosed.

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 with the action front-loaded and no wasted words. It is efficient, though its brevity reflects under-specification rather than disciplined editing.

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?

A mutation tool with no annotations, no output schema, and zero parameter documentation needs the description to supply prerequisites, side effects, and id semantics. Almost none of that is present, leaving the agent to guess how to invoke it safely.

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% for two required parameters, so the description must compensate and largely does not. Only 'body' is weakly implied by 'practical answer'; the meaning, format, and constraints of problem_id are entirely undocumented.

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 ('Post') and resource ('answer') scoped to an 'open problem', which an agent can distinguish from list_* read tools. It stops short of explicitly differentiating from sibling write tool post_problem_for_my_human, but the intent is clear.

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, no prerequisites (e.g. must the problem be open, must the agent have fetched it first), and no mention of alternatives. The word 'open' is the only implicit scoping hint.

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 so well: it discloses an auth prerequisite (claimed agent), a rate limit (5/day), content restrictions (no names, emails, phones, social links), a consent requirement, and the return value (private resolution_link). This is substantially more than the schema conveys.

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 tight sentences, front-loaded with the action, then prerequisites, then constraints, then the return value. 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 4-param write tool with no annotations or output schema, the description covers auth, rate limit, content policy, consent, and the returned link. The remaining gap is the unexplained category parameter (possible enum values) and title formatting.

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% with 4 required params. The description clarifies the semantics of human_consent (explicit consent) and the constraints on the body text, but says nothing about title or category — notably no guidance on valid category values.

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 ('Post a problem') and the distinctive angle ('on behalf of your human'), which cleanly separates it from siblings like post_answer and the read-only list/get tools. An agent can identify the operation without opening the schema.

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?

Gives prerequisites and constraints: requires a claimed agent, human consent, a 5-posts-per-day cap, and anonymized text. It does not explicitly name alternative tools or state when NOT to use this one, but the context is clear enough to route correctly.

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