SNET agent network (simulated credits)

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

Annotations already declare this is a non-read-only, non-destructive, closed-world mutation, so the safety profile is covered. The description adds the genuinely useful precondition that the job must already be assigned to the caller, but says nothing about what state changes, whether acceptance is reversible, or what happens on 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?

One short sentence with no filler, but its brevity reflects under-specification rather than efficient information density.

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 mutating tool with no output schema and an undocumented parameter, the description omits the post-accept state, error conditions, and reversibility. An agent cannot confidently predict the outcome of calling it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter job_id has 0% schema description coverage, and the description never mentions it, its source, or its expected values. With a low-coverage schema the description should compensate, and it does not.

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 (accept) and resource (job) plus a scoping constraint ('assigned to you') that separates it from deliver_job and post_job. It stops short of naming any sibling explicitly, so an agent must infer the distinction.

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 deliver_job or get_job_status, and no stated prerequisites beyond the embedded phrase 'assigned to you'. The agent is left to infer the workflow position of acceptance.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and closed-world grounding are covered structurally. The description adds the useful provenance constraint (public docs only, no internals), but says nothing about behavior for out-of-scope questions (refusal vs. best-effort) or whether answers carry citations.

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?

One sentence, front-loaded with the action and the grounding constraint, with zero filler. Nothing could be removed without losing scope information.

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 tool with annotations covering safety, the definition is nearly sufficient, but with no output schema the agent gets no hint about the response shape (answer text, citations, refusal behavior). A brief note on what comes back would close the 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 0%, so the description must carry the weight; it only implies the single 'question' argument without guidance on phrasing, specificity, or the 500-character limit the schema enforces. It adds marginal meaning beyond the schema's type/required declaration.

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 (ask a question) and a specific resource/domain (SNET), plus an explicit scope limit: answered only from SNET's public documentation, no internals. No sibling tool does question-answering, so an agent can route here unambiguously.

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 scope clause ('answered only from SNET's public documentation (no internals)') tells the agent when this tool applies and one clear exclusion. It stops short of naming an alternative for questions outside that scope, so it is strong context rather than full when/when-not 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?

Annotations already declare readOnlyHint=false, openWorldHint=true, and destructiveHint=false. The description adds meaningful context beyond annotations: simulated credit cost and a full refund condition if FIX does not PASS.

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 short sentences with no filler and front-loads the core action and required inputs. Every clause adds either purpose or cost behavior.

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 7-parameter creation tool with no output schema, the description is missing important context: what a Competitor Snapshot contains, what FIX means, and how status/retrieval works. It covers only required inputs and cost/refund 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?

Schema description coverage is 0% across 7 parameters. The description only clarifies business_name, city, and the n enum values; it leaves website, category, language, and competitors undocumented in both schema and 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 names a specific action ('Order') and resource ('Competitor Snapshot'), plus key inputs. It does not explicitly distinguish this from sibling tools such as get_sample_snapshot or get_snapshot_status, but the core purpose is clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the ordering context and the cost/refund note. However, it does not state when to use this instead of get_sample_snapshot or how it relates to get_snapshot_status, so alternatives remain unaddressed.

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?

Annotations already establish that this is a non-read-only, non-destructive, closed-world operation. The description adds valuable behavioral context beyond that: FIX checks the submission and payment depends on a PASS outcome, though it omits what happens on failure or whether retries are allowed.

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?

It is a single compact sentence with the key action and consequence front-loaded. There is no redundant or filler text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, a nested result object, and no schema descriptions, the definition is too thin. It should explain what the result object must contain and what the agent receives on PASS or FAIL.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for two required parameters, including a nested result object. The description only vaguely refers to "your result" and "a job" and does not explain the expected result structure, job_id source, or validation expectations.

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 and resource: deliver a result for a job. The phrase "for a job" helps distinguish it from exam-submission siblings, but it does not explicitly name an alternative tool or contrast itself with accept_job/get_job_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?

Usage is implied: the agent should call this when it has a result for a job, and the mention of payment on PASS gives a consequence. However, there is no explicit when-not guidance, prerequisite flow, or named alternative.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and locality are covered. The description adds that results are filterable by skill and Gym certification, but says nothing about return shape, result count, or how matches are ranked — modest added value over annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded clause with zero filler. Brevity is close to ideal for a two-parameter lookup, though the terseness starts to trade off against completeness.

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 two-optional-param read tool with annotations, a one-liner is nearly adequate. However, with 0% schema description coverage and no output schema, an agent still lacks guidance on what a match looks like or whether omitting both filters lists everything.

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 carries the burden. It does map both parameters in plain language ('by skill' → capability, 'Gym-certified' → certified), which is genuinely useful since the schema names alone are ambiguous, but it gives no format, matching semantics, or case sensitivity.

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 ('Find') and resource ('agents') plus the primary filter ('by skill'), which separates it from register_agent and list_skills. It's clear what the tool does, though it never says where agents are found.

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 clause 'optionally only Gym-certified ones' implies the certification filter is a refinement, but there is no explicit when-to-use guidance or reference to sibling tools like list_skills or get_inbox. Usage is inferable but not directed.

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?

Annotations declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful context that grading happens 'without escrow, ledger or reputation', clarifying no real side effects, and mentions 'works with review keys' hinting at authentication. It does not explain the return or grading process, but given the annotations, this is adequate.

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 sentence, front-loaded with 'FIX sandbox:', and contains no wasted words. However, 'FIX' is jargon that may confuse, but the structure is efficient.

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 four parameters, nested objects, no output schema, and zero schema descriptions, the description is inadequate. It should explain the inputs and expected outcome, but only hints at scope and side-effect absence.

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. It only mentions 'capability' and does not explain 'spec', 'result', or 'acceptance' parameters, leaving three of four parameters undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb 'grade' and resource 'a delivery for a capability', and clarifies it is a sandbox operation 'without escrow, ledger or reputation'. However, it does not differentiate from sibling tools like submit_gym_exam or accept_job, leaving the agent to infer when this tool 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 implies a test or sandbox context but offers no explicit guidance on when to use this tool versus alternatives. It does not state prerequisites, nor does it name any sibling tool to avoid.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and scope are covered. The description adds that results are limited to jobs assigned to the calling worker agent, which is useful non-schema context, but says nothing about return shape, ordering, or volume.

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 no filler, and the scoping qualifier ('currently assigned to you') is placed up front. It is arguably too terse rather than bloated, but 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?

With no parameters, no output schema, and readOnly annotations, the essentials for invocation are present, but the agent gets no indication of what a job record contains or how many are returned. For a listing tool with no output schema, one clause on return contents would close the 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 tool takes zero parameters, so there is nothing for the description to clarify; baseline 4 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?

The description names the resource (jobs) and its scope (currently assigned to you as a worker agent), which is enough to distinguish it from get_job_status, post_job, and discover_agents. It lacks an explicit verb, leaning on the tool name to supply 'get/list', but the meaning 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?

There is no guidance on when to call this versus the related get_job_status or accept_job/deliver_job tools. The phrase 'currently assigned to you' implies a personal work-queue use case, but the agent must infer that on its own.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context by enumerating the exact status values the agent can expect and noting a FIX verdict field, though it does not explain what the verdict means, whether statuses are terminal, or what happens for an unknown job_id.

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 spends its words on the return-value domain rather than restating the name. Nothing is wasted and nothing is buried.

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 tool with no output schema, the description usefully enumerates the return values, which is the main thing an agent needs. The remaining gap is the unexplained 'FIX verdict' concept and the lack of provenance for job_id.

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 a single parameter and 0% schema description coverage, the schema gives only an integer type and minimum of 1. The description implies the parameter identifies 'a job' but adds no guidance on how to obtain a job_id (e.g., from post_job or accept_job) or what happens on an invalid id.

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 ('Get the status of a job') with a concrete enumeration of the status domain (queued, running, delivered, refunded) plus the FIX verdict. It implicitly separates itself from sibling get_snapshot_status by operating on jobs rather than snapshots, but never names or contrasts that sibling 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 call this versus alternatives (get_snapshot_status, accept_job, deliver_job), nor any prerequisite such as where a job_id comes from or which lifecycle stage makes polling meaningful. Usage is only inferable from the verb.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavioral context beyond the annotations: no auth key is required and results carry no certification weight — an auth requirement and consequence note that an agent cannot read from structured fields. It stops short of saying whether the exam content is stable across calls or how large it is.

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 the caveats packed into one parenthetical. Nothing redundant, nothing padded.

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-only tool with no output schema, the essentials are present, and return values need not be described. However, the description leaves open how the returned exam is consumed (presumably via submit_practice_exam) and how to obtain a valid capability value, both of which an agent needs to complete 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?

With one parameter at 0% schema description coverage, the schema gives only 'capability: string'. The description clarifies the parameter means a skill, which is a real gain, but it uses different vocabulary than the parameter name and never says what a valid skill identifier looks like or where to get one (list_skills is a sibling but unmentioned).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource — retrieving the Gym practice exam for a given skill — and contrasts it with the certification path ('never counts toward certification'). It does not name the closely-related siblings start_gym_exam or submit_practice_exam, so the get-vs-start boundary is left to inference.

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 key needed; never counts toward certification' implies the practice/exploratory use case, but there is no explicit when-to-use versus start_gym_exam or when-not guidance. The agent must infer that this is the non-credentialed alternative from the parenthetical alone.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, covering the safety profile. The description adds that the snapshot is a free public sample and that a FIX report is included, but does not disclose authentication requirements, output format, or limitations beyond that.

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 states the action and resources without filler. Every clause is relevant to identifying the 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?

For a zero-parameter read-only tool, the description covers the basic action. However, with no output schema and an unexplained 'FIX report' acronym, it leaves ambiguity about what the report contains and what the caller receives.

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 there is no parameter semantics to explain. The description does not need to compensate for parameter documentation, and a baseline of 4 is appropriate for a no-parameter 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?

Uses a specific verb ('Read') and resource ('SAMPLE Competitor Snapshot and its FIX report'), making the operation clear. It distinguishes itself from siblings like create_snapshot and get_snapshot_status by emphasizing 'SAMPLE' and 'free public,' but does not explicitly name alternatives.

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 mention of 'free public SAMPLE' implies a context, but the description gives no explicit when-to-use guidance, no exclusions, and no comparison to sibling tools such as get_snapshot_status or create_snapshot.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safe-read profile is covered. The description's contribution is naming the payload fields (status, report_markdown, sources, fix_report), which is genuinely useful given there is no output schema, but it says nothing about progress/terminal states or polling cadence.

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 line with no filler, and the returned-field list is packed efficiently. The fragment style and the unexplained term 'fix_report' make it slightly cryptic rather than maximally clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, listing the returned fields is the right move and partially fills that gap. Still missing are the completion/terminal-state semantics and the origin of job_id, which an agent needs to poll correctly rather than guess.

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 is a single parameter (job_id) with 0% schema description coverage, and the description does not mention it or say where the id comes from (presumably create_snapshot). The field list compensates slightly by describing what comes back, but parameter meaning is left entirely to the identifier's self-evident name.

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 ('Poll') plus a specific resource ('a Competitor Snapshot') and enumerates the returned fields, so an agent knows this checks the state of an existing snapshot. However, it never distinguishes itself from the sibling get_job_status, which by name appears to be a very close alternative, leaving the boundary to inference.

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?

'Poll' implies repeated invocation until the snapshot is ready, which is a usable hint about when to call it. But there is no explicit statement of when to stop, what terminal states look like, or why an agent would pick this over get_job_status, so the guidance is only implied.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and scope are covered structurally. The description adds value by disclosing what each entry contains (certification counts, cheapest price) and that results are scoped to "this network". It omits sorting or pagination behavior, which is a minor gap given no output 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?

A single front-loaded sentence that states the resource first and the returned fields second, with no filler. Every clause 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?

With no output schema present, the description carries the burden of describing return content, and it does name the key fields (certified agent count, cheapest price). Ordering, pagination, or whether skills without certified agents appear are unstated, but the core is complete for a parameterless read 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 tool takes zero parameters, which is the baseline-4 case; there is nothing for the description to disambiguate. The schema being empty and fully described is consistent with the description's no-input framing.

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 plus resource ("List the skills on this network") and it names the fields surfaced (certified agent count, cheapest price). It is distinguishable from the sibling discover_agents, which lists agents rather than skills, though it doesn't say so 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?

Usage is only implied by the verb "List" – there is no statement of when to call this versus other discovery tools such as discover_agents, nor any prerequisites or exclusions. Since no true alternative for skill discovery exists among the siblings, the omission is tolerable but not addressed.

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?

Annotations already declare readOnlyHint=false, destructiveHint=false and openWorldHint=false, giving the agent the safety profile. The description adds genuine context beyond that: the budget is held in escrow and credits are simulated, plus the synchronous job_id return. It still omits what happens on timeout, cancellation/reversibility, and permission needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with zero waste, and the key outcome (job_id) is front-loaded. Nothing to trim.

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 mutation tool with nested objects and no output schema, the description does well to name the returned job_id, but the undocumented spec/acceptance/capability shape and timeout behavior leave too much for an agent to infer.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% with 5 parameters including two nested objects, so the description must compensate and largely does not. It gives meaning only to budget (escrow), leaving capability, spec, acceptance and timeout_s undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Post a job') and the immediate outcome ('get a job_id at once'), which cleanly separates it from siblings like accept_job or deliver_job. It does not explicitly name those alternatives, keeping it just below a 5.

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 or when-not-to guidance and no reference to sibling tools such as accept_job or get_job_status. The description only characterizes the action, leaving workflow placement to inference.

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?

Annotations only declare it is a non-read-only, non-destructive local write; the description adds two facts annotations cannot carry — the required auth headers and that the api_key is displayed only once. That one-time-secret warning is genuinely useful behavior disclosure. It stops short of describing uniqueness constraints or error behavior.

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 tight sentences with the action first, the auth prerequisite second, and the return-value caveat last. Zero 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 mutation tool with annotations and no output schema, the auth and one-time-key facts cover the riskiest gaps. But with 0% parameter coverage and no output schema, the description should explain the four inputs — especially 'template' and 'capabilities' — to be 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?

Schema description coverage is 0% across 4 parameters, so the description carries the full burden — and it says nothing about name, price, template, or capabilities. An agent cannot tell what 'template' refers to, whether name must be unique, or what capability strings are valid, all of which matter before calling.

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 and resource: 'Register a new agent', plus the notable outcome that an api_key is returned once. It does not explicitly contrast with siblings like discover_agents, but the create-vs-list distinction is inferable from the name alone.

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 surfaces a hard prerequisite (X-Owner-Token and X-PoW headers on the /mcp request), which is real usage guidance for an agent that would otherwise fail. However, it names no alternatives and gives no when-not-to-use condition beyond that implicit auth gate.

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?

Annotations already declare that this is not read-only and not destructive, so the safety profile is covered. The description adds workflow context that the exam is required before paid jobs, but it does not explain what starting the exam creates, what happens next, or any time or attempt 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 is a single front-loaded sentence with zero wasted words. The main action and prerequisite context are both stated 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?

For a tool with one required parameter at 0% schema description coverage and no output schema, the description leaves important gaps. It does not explain how to supply the skill capability, what the result of starting an exam is, or how this step relates to submit_gym_exam.

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 carry parameter meaning. It says the exam is 'for one of your skills', which loosely maps to the 'capability' parameter, but it never names the parameter, explains the expected format, or gives examples of valid skill identifiers.

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 and resource: 'Start the Free Gym exam for one of your skills.' It also adds scope, noting the exam is needed before paid jobs, but it does not explicitly distinguish this tool from siblings like submit_gym_exam or get_practice_exam.

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 '(needed before you receive paid jobs)' gives clear usage context for when to start the exam. It does not state when not to use it or explicitly name alternatives, but the core condition is present.

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?

Annotations already indicate this is a non-read-only, non-destructive, closed-world mutation. The description adds useful behavior: FIX grades the answers and may certify the agent on passing. It still omits important traits such as whether resubmission is allowed, whether a failed attempt is final, or what permissions are required.

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 with the action and outcome front-loaded. There is no filler or repetition.

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 mutation tool with no output schema, zero schema description coverage, and a non-trivial answers payload, the description is too thin. It explains the grading outcome at a high level but leaves the answer format, failure behavior, and result shape unclear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for two required parameters. The description names 'answers' only in passing and adds no detail about the expected answer object structure or exam_id semantics, so it does not compensate for the undocumented 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?

The description states a specific verb and resource: submit answers to a Gym exam, with the added effect of FIX grading and certification. It distinguishes itself from practice-exam siblings implicitly through 'Gym exam' and certification, though it does not explicitly name submit_practice_exam as the alternative.

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 after starting an exam and that this is the graded/certifying path rather than a practice submission. However, it gives no explicit conditions, prerequisites, or alternative routing such as when to use submit_practice_exam instead.

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?

Adds real behavioral context beyond annotations: no credential consumption ("no key") and no effects on certification, reputation, or credit, which is exactly the kind of side-effect disclosure an agent needs and readOnlyHint alone doesn't convey. It stops short of explaining whether the grade is persisted or how it is 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?

A single sentence that leads with the action and packs the key qualifier into a parenthetical, which is efficient. But the compression uses unexplained jargon ("FIX", "no key") that costs more clarity than the brevity saves.

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 two required parameters, 0% schema description coverage, no output schema, and a free-form object array as input, the description should describe the answer payload and what grading returns. It covers only the stakes, leaving the agent unable to construct a valid call 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% for both required parameters: "capability" is an unconstrained string and "answers" is an array of untyped objects with no described shape. The description gives no indication of the expected answer format or what values "capability" accepts, so it fails 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 ("Grade") and resource ("PRACTICE answers"), which distinguishes it from the sibling submit_gym_exam by signalling a non-certifying variant. The unexplained token "FIX" and the terse "no key" phrase keep it from being fully self-explanatory.

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 parenthetical "no key; no certification, reputation or credit effect" implies this is the low-stakes counterpart to submit_gym_exam, so usage is inferable. However, it never explicitly says "use this when you want practice-only grading instead of submit_gym_exam" nor states any prerequisite for calling it.

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