GeniusFlow Evidence

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

With no annotations provided, the description must carry the burden of behavioral disclosure. It reveals the HTTP methods (GET/POST), which imply read vs. write, but omits side effects, permissions, error behavior, or return characteristics. This is a significant gap for a tool involving both query and mutation.

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 with no filler or repetition. It conveys the two modes and the packet shape efficiently, making every word meaningful.

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 absence of annotations and output schema, the description is too terse to be complete. It leaves unanswered how the GET response is structured, how id interacts with GET vs POST, what 'cite packet' contains beyond the listed fields, and what errors or prerequisites exist. The tool has moderate complexity (3 params, nested object) that warrants richer context.

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 description adds the packet structure '{kind,id,claim?}', giving purpose to the parameters beyond the sparse schema. However, it does not clarify the role of 'id' in the GET context or the exact conditions for each parameter, and schema coverage is only 33%, so the description 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?

The description clearly identifies two distinct operations: GET the cite catalog or POST a cite packet, with the packet shape explicitly specified. This verb+resource structure is specific and differentiates the tool from siblings like gf_dossier or gf_verify.

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 GET vs POST distinction implies when to use each operation, and the schema hints that setting 'kind' triggers POST. However, there is no explicit guidance about alternatives or conditions for choosing between fetch and create beyond this, and no mention of related tools.

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?

The description explicitly indicates a GET operation and 'public' data, which implies a read-only and accessible behavior. However, it lacks details such as return format, error conditions, or rate limits. With no annotations, the description carries the full burden but only partially fulfills it.

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, tightly written sentence that front-loads the core purpose (GET public Darshan) and appends concise details in parentheses. Every word contributes to understanding.

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 GET tool with no output schema, the description provides enough context about the resource and what it contains. It lacks an explicit return structure, but the included details about its contents are sufficient for a simple retrieval 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 input schema has zero parameters, so the baseline is set to 4. The description adds context about the resource content but does not need to document any parameters since none exist.

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 performs a GET operation for public Darshan, specifying the contents (refuse/admit samples and provenance rail). It is specific about the resource and action, but does not explicitly distinguish this from sibling tools.

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 is provided about when to use this tool versus alternatives, nor any exclusions or prerequisites. The description is purely declarative with no usage context.

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?

GET explicitly signals a read operation, and the note about claims[] when ledger-backed and additive projection keys adds some behavioral detail. However, with no annotations, important behavior such as failure modes, auth, pagination, and meaning of Ring 1 walkers remains unspecified.

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 consists of two short, front-loaded sentences with no filler. The first sentence gives the core contract, but the second sentence is compact to the point of being cryptic, preventing a top score.

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 operation, the schema plus the operation-level description is enough to make a basic call. Still, there is no output schema and the description relies on unexplained terminology such as ledger-backed, public_entity_projection.v1, and Ring 1, leaving noticeable gaps about response shape and behavior.

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 already fully documents the only parameter as a required entity codename string, with example AAVE_V3, so 100% parameter coverage exists. The description does not add meaning beyond calling it an entity, which duplicates the schema, so it stays at the 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?

The description states a specific GET operation on an entity dossier card, and the schema example AAVE_V3 clarifies the input. It is not tautological and the resource is distinct from sibling tool names, but it does not explicitly differentiate itself from gf_status, gf_verify, or similar sister tools.

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 named when-to-use guidance, no exclusion criteria, and no reference to alternatives among siblings. The only usage signal is inferred: calling this tool fetches an entity dossier. The Ring 1 walkers phrase is too domain-specific to serve as reliable guidance.

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 of behavioral disclosure. It only says 'GET', which implies a read-only operation, but does not explicitly state that no data is modified, what format the response takes, or any potential limitations (e.g., caching, authentication requirements). This is minimal disclosure for a tool with zero annotation support.

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 essential purpose without any filler. Every word earns its place, and it is immediately scannable.

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 low complexity (no parameters, no output schema, simple retrieval), the description is sufficiently complete for an agent to understand what to expect. The OpenAPI 3 format is well-known, and the scope 'for federation endpoints' provides necessary context, though it could mention that the response is a JSON document.

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 description is not required to explain any. The baseline of 4 applies because no parameter information is needed; the tool is inherently parameterless.

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 retrieves an OpenAPI 3 document for federation endpoints. The verb 'GET' and the resource 'OpenAPI 3 document' are specific and distinguish it from sibling tools like gf_status or gf_verify, which clearly serve different purposes.

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 is provided on when to use this tool versus alternatives. While the resource type itself is distinctive, the description does not specify context (e.g., 'use this to discover available federation endpoints') or mention any exclusions or prerequisites.

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 must carry the burden of behavioral disclosure. It states the return value ('disposition + versioned proof_shape') but does not reveal whether the operation is read-only, mutates state, requires special permissions, or has side effects. The verb 'Package' is ambiguous as to whether it modifies the claim.

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 extremely concise, containing just two sentences. It front-loads the action and resource, then immediately states the return. Every word contributes to understanding the tool's function, 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 tool with one parameter and no output schema, the description provides a reasonable level of context by stating the purpose and return format. However, it lacks explanation of what 'disposition' values are allowed (e.g., 'admit' vs 'refuse'), what 'proof_shape' contains, and any behavioral or prerequisite information. The absence of annotations and output schema leaves gaps, though the simple parameter count mitigates incompleteness.

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 already provides full coverage for the single parameter 'claim' with the description 'Published claim from dossier claims[].' The tool description adds minimal semantic value by referring to 'published claim object,' but does not elaborate on required fields, constraints, or the structure of the claim beyond what the schema already states.

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 action 'Package' with a resource 'published claim object' and clarifies the intent with 'disposition admit/refuse.' It also mentions the return value, distinguishing it from sibling tools like gf_verify or gf_cite. However, 'Package' is somewhat uncommon as a verb, making it slightly less explicit than a tool like 'create' or 'update.'

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 phrase 'over a published claim object' implies the intended use case (operating on published claims from a dossier), providing implied usage context. However, it does not explicitly state when to use this tool versus alternatives such as gf_status or gf_verify, nor does it provide exclusions or conditions.

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 must disclose behavior. It indicates a GET operation (suggesting read-only) but does not mention side effects, authentication, rate limits, or response structure. Minimal transparency beyond the HTTP verb.

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 clear sentence with no redundancy. Every word contributes to the purpose, making it 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?

The tool is simple with one parameter, but 'bundled report feed' is vague. Without an output schema, the description should clarify what the feed contains or how the entity is specified. It leaves significant gaps for an agent to understand the tool's full behavior.

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 one parameter 'entity' with no description (coverage 0%). The description mentions 'for an entity', providing some meaning for the parameter but not detailing format or expected values. It partially compensates for the lack of schema 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 clearly states the action (GET), the resource (bundled report feed), and the scope (for an entity). It distinguishes this tool from siblings, which focus on other functions like citation, dossier, or status.

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 is provided on when to use this tool versus alternatives. The description only defines what it does, leaving the agent to infer usage from the name and context.

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 must carry transparency. It explicitly states '(read)', indicating a non-mutating operation, but provides no details on side effects, return format, or behavior of the 'ack ring'. Minimal disclosure.

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 with no wasted words. It efficiently conveys the method and read-only nature, though at the cost of clarity.

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 is simple, but the description fails to explain what the 'return-wire consumption ack ring' is, what the response contains, or when to use it. The lack of output schema means the description should compensate by explaining return values, which it does not.

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% for the single 'limit' parameter, so the baseline is 3. The description adds no parameter semantics beyond the schema's 'Optional limit hint'.

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 (GET) and resource ('return-wire consumption ack ring'), adding specificity beyond the tool name. However, the resource is cryptic domain jargon, and it does not differentiate from sibling tools beyond the name.

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 is provided on when to use this tool, what alternatives exist, or any prerequisites. The one-sentence description gives no context for selection among the gf_* siblings.

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 of behavioral disclosure. It enumerates output fields, providing some idea of what the user will receive, but does not mention side effects, permissions, error conditions, or whether network calls are made. This is minimal transparency.

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 compact sentence, front-loaded with the main function and a list of included items. It is economical with no filler, though it is a fragment rather than a full sentence.

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 has no parameters and no output schema, the description is the sole source of information. It lists several output fields, but terms like 'endpoint health' and 'honest tier' are left undefined, leaving some ambiguity. It is adequate for a simple status 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 has zero parameters, so per rubric the baseline is 4. The description does not need to elaborate on parameter meanings, and the input schema confirms there are none.

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 identifies the tool as providing Federation SLA/status and lists specific fields returned (build_id, bake time, endpoint health, honest tier). While it lacks an explicit verb, the subject matter is unambiguous, and the content list distinguishes it from generic sibling tools.

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 is given on when to use this tool versus any alternatives. The only hint is the word 'status', which implies querying for status but does not explicitly explain appropriate contexts 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 burden of behavioral disclosure. It reveals an important constraint (inputs must come from published claims), warns against a common mistake, and states the return value ('proof_shape'). This is valuable context beyond the schema.

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 extremely concise (three short sentences) and front-loaded with the core purpose. Every sentence adds value: the action, the constraint, and the return type. 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?

The tool has four parameters, a nested object, and no output schema or annotations. The description gives the essential invariant and return value but lacks detail on parameter usage patterns, potential errors, or when to use this tool relative to siblings. It is adequate but not comprehensive.

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 low (25%: only 'claim' has a description). The description clarifies that 'source_url' and 'expected' must come from published claims, adding meaning for two of the four parameters. However, it does not explain 'location' or the 'claim' object's structure beyond what the schema provides.

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 the tool's core action ('Re-check grounding') and identifies the key inputs (source_url + expected). It is clear and specific, though it does not explicitly distinguish it from sibling tools like gf_cite or gf_darshan.

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 usage context (verifying grounding against published claims) and provides a caution ('Do not invent expected from report HTML'). However, it does not explicitly state when to prefer this tool over alternatives or when not to use it.

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