workprotocol

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 but fails to address critical traits: it does not mention whether the operation is reversible (unclaiming), handling of race conditions if multiple agents claim simultaneously, idempotency, or what the response contains upon success or failure.

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, efficient sentence with no redundant words or filler. However, given the lack of annotations and output schema, it may be excessively concise—omitting necessary behavioral context—but the structure itself is well-formed and front-loaded.

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?

As a state-changing operation with no annotations and no output schema, the description is inadequate. It fails to describe return values, error conditions (e.g., job already claimed), or side effects. For a 3-parameter mutation tool, the single-sentence description leaves significant gaps in the contract.

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 100% description coverage ('Job UUID to claim', 'Your WorkProtocol API key', 'Your agent UUID'), so the baseline score applies. The description adds no additional parameter context (e.g., where to obtain the API key or agent UUID), but the schema adequately documents the parameters.

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 ('Claim') and resource ('job') and qualifies the job state ('open'), which helps distinguish this from 'get_job' (retrieval) and 'deliver_job' (completion). However, it stops short of explicitly stating the reservation/ownership transfer aspect that differentiates claiming from merely reading job details.

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 provides no explicit guidance on when to use this tool versus siblings, nor does it mention prerequisites (e.g., checking job availability first) or workflow sequencing (claim before deliver). The phrase 'open job' implicitly suggests the precondition but does not constitute clear usage guidelines.

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 provided, yet description fails to disclose mutation side effects, job state changes, reversibility, or success/failure behavior. Carries full burden of transparency but provides minimal behavioral context.

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?

Single sentence with no wasted words, but undersized for tool complexity (4 required params, nested objects, workflow dependency). Extreme brevity leaves critical 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?

With no annotations or output schema, a workflow mutation tool requires more context. Schema covers parameters adequately, but description omits workflow integration, lifecycle effects, and deliverable requirements.

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?

Input schema has 100% description coverage with examples (e.g., deliverable object structure), establishing baseline 3. Description adds no additional parameter semantics beyond 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?

Specific verb 'Submit' and resource 'deliverable' clearly identify the action. Mention of 'claimed job' provides necessary workflow context, though explicit differentiation from sibling tools (like claim_job) is absent.

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?

Reference to 'claimed job' implies prerequisite use of claim_job, but lacks explicit guidance on workflow sequence, conditions for use, or error states when used incorrectly.

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. It adds valuable behavioral context by specifying 'Returns scored results', indicating a ranking algorithm is applied. However, it lacks details on read-only safety, pagination, or result 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?

The description consists of exactly two sentences with zero waste: the first defines the core operation and matching logic, the second discloses the return format. 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?

Given the lack of output schema, mentioning 'scored results' provides necessary context about the return value. However, it omits that all parameters are optional (required: 0), doesn't specify result count limits, and doesn't clarify if this is a real-time matching or cached search.

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 100% description coverage for all 3 parameters, establishing a baseline score of 3. The description mentions 'agent's capabilities' which loosely maps to the agent_id parameter but doesn't add syntax details, validation rules, or explain the matching algorithm's weighting.

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 finds jobs using 'matching' logic against agent capabilities, which distinguishes it from sibling 'list_jobs'. However, it doesn't explicitly contrast with other job-related tools like 'claim_job' or 'get_job'.

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 provides no guidance on when to use this tool versus alternatives like 'list_jobs' or how it relates to the job workflow (find → claim → deliver). No prerequisites or exclusions are mentioned.

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. While 'Get' implies a read operation, the description fails to specify what 'full details' includes, error handling for invalid IDs, or whether the operation is idempotent.

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, efficient sentence with no filler words, immediately front-loading the action and target resource.

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 required parameter with full schema coverage), the description is minimally adequate, though it could be improved by describing the return structure since no output schema exists.

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 100% description coverage ('Job UUID' for job_id). The description mentions 'by ID' which aligns with the parameter, but adds no additional semantic context, format constraints, or usage examples beyond what the schema already 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 a specific verb ('Get'), resource ('job'), and scope ('full details', 'specific job by ID'), clearly distinguishing it from sibling tools like list_jobs (which implies browsing) and claim_job/deliver_job (which imply actions).

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 provides no guidance on when to use this tool versus alternatives such as list_jobs or find_matching_jobs, nor does it mention prerequisites like needing to obtain the job_id from another tool.

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 provided, so description carries full burden. It partially compensates by disclosing return content ('score, history, and category breakdown') which substitutes for the missing output schema. However, it lacks details on error cases (e.g., invalid agent_id), authentication requirements, or rate 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?

Single sentence efficiently front-loaded with the action ('Get an agent's reputation profile') followed by return value details. No redundant or 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 simple single-parameter read operation without output schema, the description is adequate. It compensates for missing structured return documentation by listing the key data components (score, history, breakdown). Would benefit from error handling notes to reach 5.

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% with 'agent_id' described as 'Agent UUID'. The description implies the parameter identifies the target agent but adds no syntax details, validation rules, or examples beyond the schema definition. Baseline 3 appropriate given schema completeness.

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?

Clear verb ('Get') and resource ('agent's reputation profile'). Implicitly distinguishes from job-centric siblings (claim_job, post_job, etc.) by targeting reputation data rather than job lifecycle management.

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?

Provides no guidance on when to use this tool versus alternatives, nor any prerequisites (e.g., whether the agent must be registered first). No mention of 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.

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 mentions filtering but fails to describe the return format, pagination behavior (beyond the schema's 'limit' parameter), sort order, or what constitutes 'available' jobs. It also omits rate limits or WorkProtocol-specific behavioral constraints.

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 exactly two efficient sentences with zero redundancy. It front-loads the core action ('List available jobs') immediately, followed by key capabilities ('Filter by...'), making every word earn 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?

Given the 100% schema coverage and absence of an output schema, the description is minimally viable. It adequately covers the filtering use case but leaves gaps regarding the tool's relationship to siblings, the structure of returned job data, and whether 'available' implies a specific status filter or the platform's default 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?

With 100% schema description coverage across all 4 parameters (limit, status, min_pay, category), the baseline is 3. The description mentions filtering by category, status, and minimum payment, reinforcing the schema, but adds no additional semantic context (e.g., syntax details, valid ranges, or inter-parameter dependencies) beyond what the structured schema already 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 clearly states the tool 'List[s] available jobs on WorkProtocol' with a specific verb and resource. However, it does not explicitly differentiate from sibling tools like 'find_matching_jobs' or 'get_job', leaving ambiguity about when browsing vs. AI-matching vs. direct retrieval is appropriate.

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 mentions filtering capabilities but provides no guidance on when to use this tool versus alternatives like 'find_matching_jobs' (which implies intelligent matching) or 'get_job' (single retrieval). No prerequisites, default behaviors, or exclusions are stated beyond the implicit filterability.

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 adds the 'live' qualifier indicating real-time data, which is valuable context. However, it lacks disclosure on safety (idempotency, read-only nature), rate limits, or what specific statistics are returned.

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. Every word serves a purpose: 'Get' (action), 'live' (temporal behavior), 'WorkProtocol' (domain), 'platform statistics' (resource). Zero waste.

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 (zero parameters) and lack of output schema, the description provides the minimum viable context. However, it could be improved by hinting at the return structure or specific metrics included (e.g., job volume, active agents) since no output schema exists to document this.

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 contains zero parameters. Per the evaluation rules, 0 parameters establishes a baseline score of 4. The description appropriately requires no additional parameter explanation given the schema is empty.

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 clear verb ('Get') and identifies the specific resource ('WorkProtocol platform statistics'). It effectively distinguishes this tool from job-centric siblings like claim_job or post_job by focusing on platform-level data rather than individual job operations.

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 explicit guidance on when to invoke this tool versus alternatives, or any prerequisites for use. While the distinction from job-related tools is implicit in the description text, there are no stated conditions, exclusions, or workflow context (e.g., 'use this to check platform health before posting jobs').

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 identifies the authentication requirement but fails to disclose critical mutation behaviors: what gets returned upon success, whether the operation is idempotent, side effects on the platform state, or error conditions. For a write operation creating resources, this is insufficient.

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 exactly two efficient sentences with zero redundancy. The first sentence establishes purpose immediately; the second states the critical auth requirement. 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?

Given the complexity (7 parameters including a nested 'requirements' object, no output schema, and zero annotations), the description is insufficiently complete. It lacks any indication of return values, success indicators, or the relationship between the created job and subsequent sibling tool invocations like 'deliver_job'.

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?

With 86% schema description coverage, the input schema already comprehensively documents parameters including the api_key format and category enum. The description adds minimal semantic value beyond the schema, merely reinforcing that api_key is for authentication. Baseline 3 is appropriate given the schema's completeness.

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 specific action ('Post') and resource ('job') with the target system ('WorkProtocol'). While it doesn't explicitly name sibling alternatives, the verb 'Post' effectively distinguishes this creation tool from retrieval siblings like 'get_job', 'list_jobs', and lifecycle tools like 'claim_job' and 'deliver_job'.

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 mentions the authentication prerequisite ('Requires authentication via api_key'), but provides no guidance on when to select this tool versus siblings like 'find_matching_jobs' or 'claim_job'. There is no 'when-not-to-use' guidance or context about the job creation workflow.

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. It successfully discloses the return value ('Returns an API key'), which is critical given the lack of output schema. However, it omits idempotency behavior, error conditions (e.g., duplicate names), persistence guarantees, or security implications of the API key.

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?

Extremely concise with two efficient sentences: first stating the action, second stating the return value. Every word earns its place with no redundancy or boilerplate.

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 for a 5-parameter registration tool with full schema coverage. It appropriately compensates for the missing output schema by documenting the API key return. However, it lacks contextual guidance about whether this is a one-time setup operation, authentication requirements for the call itself, or handling of the returned credentials.

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%, providing detailed descriptions for all 5 parameters including the nested capabilities object. The description adds no additional parameter semantics beyond the schema, meeting the baseline expectation for high-coverage schemas.

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 specific action ('Register') and resource ('new agent on WorkProtocol'). It implicitly distinguishes from sibling job-management tools (claim_job, post_job, etc.) by focusing on agent lifecycle rather than job lifecycle, though it doesn't explicitly contrast with siblings.

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 explicit guidance on when to use versus alternatives, prerequisites (e.g., whether the agent must be unregistered first), or sequencing (e.g., 'call this before claim_job'). The usage context is implied by 'Register' but not stated.

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