AB[500] research and bounties

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does enumerate the returned fields and identifies the input key, which is useful. However, it does not clarify snapshot semantics, potential absence of data, or any read-only guarantees beyond the inherent meaning of 'Get'.

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 well-structured sentence that front-loads the core action, resource, and key output fields. Every phrase carries meaning, with no filler or redundant restating of the 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 simple single-parameter getter with no output schema, the description is largely complete: it identifies the input and lists what data will be returned. Minor gaps include no mention of empty results or error behavior, but these are not critical for this 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 input schema already fully describes the single 'slug' parameter with an example, so the description adds little beyond restating 'by AB5D artist slug'. With 100% schema coverage, the baseline of 3 is appropriate; the description does not introduce new parameter meaning.

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 specifies a precise action ('Get') with a clear resource ('one artist's oTDH rank, score, collector breadth, raw collector-days, project count, and snapshot metadata') and input method ('by AB5D artist slug'). This clearly distinguishes it from list_artist_otdh, which suggests a plural/list operation.

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 implies use when retrieving a single artist's oTDH data by slug, and the singular framing differentiates it from listing tools. It does not explicitly name alternatives or exclusion criteria, but the context is clear enough for an agent to select it appropriately.

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 provided, the description carries the full burden of disclosure. It reveals that the tool returns status and operational routes, and it warns about a critical behavioral constraint: work should not begin unless the status is open. This goes beyond a simple 'get by ID' and gives the agent actionable behavior guidance, though it does not cover error cases or auth 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?

The description is two sentences long, front-loaded with the core action and resource, and every sentence earns its place. The first sentence defines purpose and contents; the second provides a critical usage warning. No filler or redundancy.

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 tool with one parameter, no annotations, and no output schema, the description is sufficiently complete. It names the returned fields (status, operational routes) and tells the agent how to act on the result ('Do not begin work unless the returned status is open'). A brief note on what happens if the task is not found or if the status is not open would improve it, but this is not a major gap.

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 defines task_id as 'Task identifier from list_open_bounties, e.g. MA-CAL-CT-01'. The description only says 'by identifier', adding no meaningful detail beyond the schema. This matches the baseline of 3 for high schema coverage.

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 clearly states a specific verb and resource: 'Get one AB5D bounty task by identifier' and specifies what is included ('current status and operational routes'). This distinguishes it from sibling tools like list_open_bounties and search_artists, which operate on collections rather than a single task.

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 gives clear context for when to use the tool: when you have an identifier and need the current status before starting work ('Do not begin work unless the returned status is open'). However, it does not explicitly name alternatives or exclusions, such as 'use list_open_bounties to find identifiers first', which keeps it just below a perfect score.

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 full burden. It discloses the return content (subtitle, essay, identity, works, images, bibliography) and licensing ('Prose is CC0'), which is useful behavioral info. It does not explicitly state it is read-only, but the verb 'get' implies it, and no contradictions exist.

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, well-structured sentence that front-loads the core purpose and then lists the content components. Every phrase earns its place with no redundancy or 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 simple one-parameter get-by-slug tool, the description adequately enumerates all returned content areas. It does not mention error behavior or pagination, but these are not essential given the tool's low complexity and explicit output listing.

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 schema already describes the slug parameter including its source and example. The description only repeats 'by slug' and adds no additional semantic information, so it matches the baseline of 3.

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 uses a specific verb ('Get') and a clear resource ('one artist's full structured biography by slug'), and enumerates the exact content included (subtitle, essay prose, identity, works, images, bibliography). This clearly distinguishes it from list/search siblings by targeting a single artist with full detail.

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 gives clear context for when to use it: when you need a full biography for a single artist by slug. It does not explicitly name alternatives or state when-not-to-use, but the parameter description in the schema adds guidance about obtaining the slug from list_dossiers/search_artists.

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 of behavioral disclosure. It enumerates the returned data items but does not explicitly state that this is a read-only operation or mention any side effects or auth requirements. Given the 'Get' verb, it may be inferred, but it is not explicitly 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, well-structured sentence that front-loads the action and lists all specific deliverables. It is concise, contains no fluff, and every word 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 tool with no parameters, no output schema, and no annotations, the description fully explains what the tool provides: definition, formulas, coverage, limitations, URL, and metadata. This is complete for the tool's simple nature.

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?

There are zero parameters, so the baseline is 4. The description adds meaning by detailing what the tool returns, which is sufficient. No parameter explanations 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 clearly uses the verb 'Get' plus a specific resource: the definition, formulas, full-universe coverage, limitations, discussion URL, and snapshot metadata for a named metric. This distinguishes it from sibling tools like get_artist_otdh or list_artist_otdh, which would return values or lists.

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 specifies the exact metric and what content is returned, providing clear context for when to use it. It does not explicitly state 'use this instead of get_artist_otdh for methodology', but the name and content make the distinction self-evident, so the context is adequate without 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?

No annotations are present, so the description must convey behavior. It adds context by defining oTDH and explaining the ranked list scope, but it does not disclose return fields, ordering details, pagination, or any side effects. A simple read-only list is implied, but not fully detailed.

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, front-loaded with the action and resource, and a concise definition of oTDH. Every sentence earns its place with no redundancy.

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 tool with one optional parameter and no output schema, the description is quite complete: it covers scope, ranking, and the meaning of the limit. It falls short of naming the exact return format, but given the simplicity and sibling context, this is a minor gap.

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 has no description for the 'limit' parameter (0% coverage). The description compensates by explaining that the tool can return 'all 308' or a 'limited leading subset,' which implies the limit controls the subset size. It does not explicitly state the default or that it is top-ranked, but it adds meaningful guidance.

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 clearly states it lists ranked oTDH records, with scope ('all 308 AB[500] artists' or a limited subset). The verb 'List' and resource are specific, and it distinguishes from the sibling 'get_artist_otdh' which is singular.

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 gives clear context: it's for listing all or a leading subset, implying use over the singular getter. It does not explicitly name alternatives or exclusions, but the list-vs-get distinction is evident from the description and sibling 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 and no output schema, the description carries the disclosure burden and does reveal the output fields and the 'published' filter. However, it does not mention behavior such as pagination, ordering, or what happens when no dossiers exist, which are plausible gaps for a list endpoint.

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 two sentences: the first front-loads the action, resource, and field list; the second adds a clear use case. There is no redundant or filler content.

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-parameter, no-output-schema tool, the description is complete: it names the operation, scope, returned fields, and recommended usage context. Nothing critical is missing 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 has zero parameters, so the schema fully covers all inputs. The description adds context about output fields and scope, but since there are no parameters, the baseline of 4 is 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 uses a specific verb ('List') and resource ('published AB[500] artist dossier'), enumerates the returned fields, and states the scope ('every published'). It also implicitly distinguishes itself from get_dossier by focusing on discovery of all dossiers rather than a single artist.

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 instruction 'Start here to discover which artists have a biography available' clearly identifies this as the initial discovery tool. It does not explicitly name alternatives, but the sibling context and the description make the intended first-step usage evident.

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 provided, the description carries the full burden of behavioral disclosure. It correctly states that only current offers are returned, which is useful. However, it does not explicitly declare the operation as read-only or safe, nor does it mention any limitations like pagination or response size. The lack of explicit safety context is a gap given no 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?

The description is a single, front-loaded sentence that conveys the core purpose and includes a secondary clarifying note. Every word is necessary; there is no fluff or redundancy. It is efficiently structured.

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 parameters, no annotations, and no output schema, so the description must carry the full context. It specifies the exact fields returned and clarifies that the list contains only current offers. It does not explain the return format (e.g., JSON array) or mention any limitations, but for a simple list operation, the provided information is adequate.

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?

There are zero parameters, so a baseline of 4 applies per instructions. The description adds no parameter information (since none exist), which is appropriate. It does explain the return fields, which indirectly clarifies that no filters 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 clearly states the tool lists open AB5D bounties and enumerates the included fields (reward, eligibility, claim route, etc.). It is a specific verb+resource ('List every AB5D bounty') that distinguishes it from sibling tools like get_bounty (single fetch) and list_dossiers (different resource).

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 implies the use case (get all currently open bounties) but does not explicitly state when to use it versus alternatives. It lacks any mention of 'use get_bounty for a specific bounty' or any exclusions. The context is clear from the verb 'list', but no direct comparison is made.

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 mentions the tool returns matching artists with slugs, which is useful, but it doesn't disclose any limitations like result count, pagination, or whether it's read-only. However, the description is clear about the search behavior, so a 3 is appropriate.

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 two sentences, front-loaded with the main purpose, and includes a usage hint. Every word earns its place, making it highly concise and well-structured.

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 the tool's simplicity (one parameter, no output schema), the description is complete enough. It explains the purpose, the return value (slugs), and the usage context. The only minor gap is not describing the output format in detail, but that's not critical for a search tool.

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 description coverage is 100% for the single parameter 'query', and the description adds an example ('Fidenza' or 'tyler') which is helpful. Since the schema already documents the parameter well, the description adds marginal value, so a baseline 3 is 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 clearly states the tool searches artist dossiers by name or keyword and returns matching artists with slugs. It distinguishes itself from siblings by explicitly mentioning the use case before get_dossier, which is a specific verb+resource combination.

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 explicitly says to use this tool before get_dossier when the exact slug is unknown, providing clear when-to-use guidance and an alternative. This is a strong usage guideline that helps the agent decide between this and sibling tools.

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