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

No annotations are provided, so the description carries the full disclosure burden. It hints at returned content (scores by skill, failure points) but says nothing about whether it is read-only, its scope, freshness, or permissions. For a zero-annotation tool this is thin.

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 that wastes no words. It is efficient, though the telegraphic style borders on under-specification rather than true conciseness.

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 simple, parameterless retrieval tool with no output schema, the description conveys the gist of what is returned. However, with no annotations and no schema, an agent still lacks scope, auth, and freshness details needed to invoke it confidently.

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. Baseline of 4 applies for a parameterless definition.

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 resource (a scorecard) and its contents – scores broken down by skill plus the points where the agent fails. This is clearer than a generic 'get' tautology, but it never differentiates itself from the retrieval-flavored siblings like get_usage.

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 call this versus siblings such as get_usage or search_library, nor any prerequisites or exclusions. The agent must infer usage entirely from the one-line description.

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 almost nothing beyond the return content. It does not state that this is a safe read-only operation, whether authentication is required, or what time window 'recent charges' covers.

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 fragment with no wasted words. The most important information (what is returned) comes first.

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 annotations and no output schema, the description is the only source of information, and it leaves 'recent' undefined and does not describe the balance format or currency. It is minimally adequate for a simple zero-parameter read tool but not fully 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?

The tool takes zero parameters, so there is nothing for the description to compensate for. Baseline 4 applies for a parameterless tool.

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 the resource clearly: 'credit balance and recent charges.' An agent can infer this returns usage/billing information, which is distinct from siblings like get_scorecard (scores) and search_library (documents). It stops short of a verb+resource phrasing or explicit sibling 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?

There is no explicit when-to-use guidance, no conditions, and no mention of alternatives such as get_scorecard. The intended usage (check your credits) is only implied by the noun phrase.

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 implies a read-only single fetch, but says nothing about permissions, error behavior when the publication is missing, or what is returned. For a bare read tool this is thin but not misleading.

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 no filler, which is structurally good. The brevity tips into under-specification given the 0% parameter coverage, but the sentence itself 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?

Two required parameters with no schema descriptions, no annotations, and no output schema, so the description is the only source of meaning — and it omits the identifier format, the return shape, and the distinction from search_library/read_rule. Inadequate for the tool's actual complexity.

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 both required parameters, and the description does not compensate. It never explains what 'publication' should be (ID, DOI, title, slug) or what form 'episode_id' takes, so the agent must guess at both required inputs.

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 ('Read'), resource ('publication'), and scope ('from the episode's library'), so the agent knows it fetches a single item. It does not distinguish itself from the sibling read_rule (same pattern, different resource) or from search_library, which likely returns multiple publications.

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 search_library (to find a publication) or read_rule (to read a rule). The 'one publication' phrasing implies a single-item lookup, but no alternatives or exclusions are named.

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. It implies a read-only operation, but says nothing about required permissions, what an episode_id represents, what happens when the section number does not exist, or the shape of the returned 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 short sentence with the core action front-loaded and a concrete example appended; nothing is redundant or padding.

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 annotations, no output schema, and 0% schema description coverage, the description is too thin for a two-parameter tool. The unexplained required 'episode_id' and the undefined error/return behavior leave an agent unable to call this confidently.

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%, so the description must compensate for both parameters. It clarifies the format of 'section' (a number such as 2143.01) but leaves 'episode_id' — a required parameter with a non-obvious meaning — entirely undefined, which is the more consequential 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 (read), resource (examination manual section), and addressing mode (by number) with a concrete example. It is distinguishable from search_rules and read_publication by the fact that it fetches exactly one section, though no sibling is named 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?

There is no statement of when to use this versus search_rules (which presumably finds the section number) or read_publication. The 'by number' phrasing weakly implies you must already know the identifier, but no condition, prerequisite, or alternative is spelled out.

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 bears the full behavioral burden. It discloses the date-scoping constraint (pre-filing publications), which is useful, but says nothing about pagination, result format, or permissions.

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 efficient sentence with the core purpose front-loaded. Nothing is wasted, though it is arguably too brief for a two-parameter search tool.

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 annotations, no output schema, and 0% parameter description coverage, the description is too thin to fully specify how to invoke the tool correctly. It explains the library's scope but leaves query semantics and return behavior entirely unaddressed.

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 both required parameters. The description only implicitly maps 'episode' to episode_id and 'search' to query, adding no syntax, format, or matching-behavior detail to compensate 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 ('Search') and resource ('episode's prior-art library'), with a parenthetical defining scope (publications before the filing date). This distinguishes it reasonably from the sibling search_rules, though it does not explicitly differentiate from read_publication.

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 tool versus alternatives like search_rules or read_publication. Usage is only inferable from the resource name; there are no stated conditions or exclusions.

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 implies a read-only search but says nothing about result ranking, pagination, result count, or how the manual is scoped, so the agent cannot predict the response shape or limits.

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 well-formed sentence with no filler and the core purpose front-loaded. It is efficient, though its brevity is partly the source of the other gaps.

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 annotations, no output schema, and both parameters undocumented, including a required episode_id whose meaning is never stated. The description is not complete enough for an agent to invoke this tool confidently in a multi-tool workflow.

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% for two required parameters. The word 'search' hints that query is a search string, but episode_id is entirely unexplained in both schema and description, so the agent has no basis for supplying it correctly.

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 (Search) and resource (examination manual for rules and tests examiners apply), which is more precise than a generic 'search' tool. However, it does not differentiate itself from the sibling search_library or explain the relationship to read_rule, so an agent must infer which search surface to use.

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 tool versus search_library or read_rule, nor any prerequisites or exclusions. The description gives no explicit context for selection, leaving routing entirely to inference from sibling names.

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 usefully discloses the return payload (episode id, instructions, tool budget), which matters since there is no output schema, but it says nothing about state effects, whether a prior episode is replaced, or any auth/permission requirements.

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, front-loaded sentences with zero filler: what it does, then what it returns. 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 an episode-initialization tool the essentials are present (action, returns, both params documented in schema), but the lack of any pruning on prerequisites, call ordering, or interaction with submit_answer leaves the agent to infer the workflow.

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 parameters are documented there, including the enum-like taskset values and the default. The description adds no parameter-level detail, so the baseline of 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+resource ('Start a new task episode') that is clearly distinct from the read/search siblings. It does not explicitly name any sibling, but no other tool in the list initiates an episode, so disambiguation is implicit.

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 call this versus the alternatives, nor any mention of prerequisites or ordering relative to submit_answer, which is presumably the counterpart that ends an episode. Usage is only inferable from the name.

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 does disclose a real constraint ('One per episode'), which is useful idempotency/cardinality information, but omits whether resubmission is rejected or replaces, whether the call ends the episode, and what a failure looks like.

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, front-loaded sentences with no waste. The core action comes first and the constraint follows immediately.

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?

Adequate but thin for a terminal submission tool with no annotations and no output schema. It never states success/failure behavior or the consequences of a duplicate submission, leaving an agent to guess at episode-ending semantics.

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 description must compensate. It adds meaningful info for 'answer' ('JSON object in the format the instructions give'), clarifying the expected shape beyond the bare schema type, but 'episode_id' is left entirely to inference.

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+resource: 'Submit the final answer' says exactly what the tool does and is clearly distinct from siblings like search_library or get_scorecard. No sibling is named explicitly, but the submission role 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?

'One per episode' and 'final answer' imply this is the terminal step of a task, giving usable context. However, there is no explicit when-to-call guidance, no note on what to do if an answer was already submitted, and no alternatives are referenced.

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