Deterministic nested hive-mind orchestration over the A2A rails: hire N solvers, adversarial cross-r
Scored across 6 tools
Each tool targets a distinct operation in the job lifecycle: solve, job_status, audit_job, verify_audit, list_solvers, and describe_agent. The closest pair is describe_agent vs list_solvers, but one describes fleet-standard agent capabilities/pricing while the other lists the registered solver pool.
All names use snake_case, and most follow a clear verb_noun or noun_noun pattern: audit_job, describe_agent, job_status, list_solvers, verify_audit. The lone exception is the bare verb solve, which is still understandable but slightly breaks the pattern.
Six tools is well-scoped for a job orchestration server. Each tool maps to a clear lifecycle or discovery operation, with no obvious filler tools.
The surface covers solving, status, audit retrieval, verification, solver discovery, and agent description. Minor gaps remain, such as no explicit job cancellation or job listing/history operation, but core workflows are covered.
Return the full content-addressed lineage of a completed job: plan, hires (including refused ones with reasons), contributions, reviews, settlements, rail calls (with simulated flags), and synthesis.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so safety is covered. The description adds real behavioral detail beyond that: the lineage is content-addressed, refused hires are included with reasons, and rail calls carry simulated flags — non-obvious traits of the payload that an agent could not get from the 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?
One front-loaded sentence with no filler; the enumerated return contents are dense but each item conveys distinct information. The long comma list is slightly hard to scan but the leading clause anchors the purpose first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return shape needn't be spelled out, and the annotations cover the safety profile. For a one-parameter read-only tool the description is nearly sufficient; only the job_id-format and job-state edge cases are left unresolved.
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 job_id parameter has 0% schema description coverage, so the description is the only source of meaning. It implies job_id identifies a completed job, but it doesn't state the identifier format, where to obtain it, or what happens if the job is not found or not yet complete.
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 verb ('Return') and resource ('full content-addressed lineage of a completed job') and enumerates the concrete artifacts returned: plan, hires, contributions, reviews, settlements, rail calls, synthesis. It does not distinguish itself from siblings like job_status or verify_audit, which plausibly overlap, so it stops short of 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?
The phrase 'of a completed job' implies a precondition (the job must be finished), which is some guidance, but there is no explicit when-to-use guidance and no mention of when to prefer job_status or verify_audit instead. The agent must infer the routing from sibling names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return fleet-standard capabilities, actions, invariants, and pricing.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds that the payload includes capabilities, actions, invariants and pricing, which hints at scope, but says nothing about size, caching, or whether the content is stable across calls — and an output schema already documents the return shape.
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 with no filler, front-loaded with the verb and the enumerated payload. It is perhaps overly compressed — 'fleet-standard' is jargon that carries meaning only to someone already familiar with the system — but nothing is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read tool with an output schema and full annotation coverage, the description only needs to convey its role in the workflow, and it does not. It never explains that this is the discovery entry point relative to solve/verify_audit, leaving the agent to infer when to call 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 tool takes zero parameters and the schema is empty, so there is nothing for the description to disambiguate. Baseline 4 applies; the description correctly implies no arguments are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Return') and enumerates the content returned: capabilities, actions, invariants, and pricing. Combined with the name describe_agent and the title 'Describe this service', an agent can tell this is the introspection/metadata tool rather than an execution tool like solve or audit_job. It stops short of a full sibling differentiation, but the resource 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 when-to-use guidance at all: nothing says whether this should be called before solve or verify_audit to discover available actions, or whether it is optional context-gathering. The alternatives are never mentioned despite five siblings in the same fleet.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return job state, plan hash, and live budget conservation books.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds the notion that the budget conservation books are 'live', implying the values change over the job's lifetime, but it says nothing about cost, latency, or whether repeated polling is cheap.
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 front-loaded sentence with no filler or redundancy. It is efficient, though the compressed phrase 'live budget conservation books' is idiosyncratic enough to be slightly ambiguous on first read.
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?
An output schema exists, so return values need not be explained, and the annotations cover safety and idempotency. What is still missing is the lifecycle link to solve and the practical guidance for a polling tool, which is material given that the only parameter is undocumented in both schema and description.
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 schema contributes only the bare name 'job_id' with no explanation. The description does not say whether this identifier comes from solve, whether it is the same id used by audit_job, or what happens if the id is unknown, leaving the single required parameter under-specified.
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 verb ('Return') and specific resources (job state, plan hash, live budget conservation books), which is far more informative than the tautological title 'Job status'. It does not explicitly differentiate itself from siblings such as audit_job or verify_audit, so it stops short of 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 statement of when to call this tool, when not to, or which sibling to prefer for audit-style inspection. An agent must infer that this is for checking on a previously submitted job rather than a post-hoc audit, and nothing in the text confirms that.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List the registered solver pool: id, kind (worker|hive), price, capabilities.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is fully covered without the description. The description adds the domain detail that 'kind' takes worker|hive values, but otherwise restates return fields already implied by the output schema, so it contributes little beyond structured data.
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 compact sentence with the resource front-loaded and no filler. The trailing field enumeration is slightly redundant given the output schema exists, but it costs little.
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 a full output schema and rich annotations, the description need not explain return shape or safety, and it is sufficient for an agent to call this correctly. The only missing piece is routing context versus solve, describe_agent and job_status.
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 per the baseline the schema carries parameter semantics entirely and there is nothing for the description to clarify. The parenthetical enum values describe output data rather than inputs, but that causes no ambiguity.
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 ('List the registered solver pool') and previews the returned fields, which cleanly separates it from siblings like describe_agent or solve. It does not explicitly name a sibling it is meant to be chosen over, so it stops short of 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?
Usage is only implied: as a zero-parameter read of the solver pool, an agent can infer it is the discovery step before solve or describe_agent, but the description never says so or excludes any alternatives. Adequate for a trivial list call, but no explicit 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.
Open and run a hive job in one call: hire solvers through the rails (covenant -> escrow -> meter), force reviewer!=author cross-review, synthesize only what survives review, settle every escrow exactly-once, and return a content-addressed audit hash plus bits-per-joule telemetry. Price: $5.00 per solve; model-backed solves have no free tier because provider cost must be covered. Sub-hires settle via escrow at each solver's list price.
| Name | Required | Description | Default |
|---|---|---|---|
| seed | No | ||
| depth | No | ||
| fee_bps | No | ||
| problem | Yes | ||
| subtasks | No | ||
| redundancy | No | ||
| request_id | No | ||
| covenant_id | No | ||
| payment_ref | No | ||
| budget_minor | Yes | ||
| accept_threshold | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations, the description adds substantial behavioral context: it hires solvers through covenant/escrow/meter rails, enforces reviewer!=author cross-review, settles escrow exactly-once, and returns an audit hash plus telemetry. It also discloses pricing and the absence of a free tier for model-backed solves, which is valuable for a paid non-read-only operation.
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 compact in sentence count and front-loads the main action, but it is dense with internal jargon such as 'rails', 'bits-per-joule telemetry', and 'covenant -> escrow -> meter'. It conveys a lot without becoming verbose, though the lack of structure makes it harder to parse for a complex 11-parameter 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 complex paid orchestration tool with 11 parameters and full schema-description gaps, the description explains the workflow and cost but leaves critical input semantics and usage boundaries undocumented. The output schema exists, so return-value detail is less necessary, but the agent still lacks enough guidance to invoke this correctly relative to its siblings.
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 11 parameters, so the description must compensate, but it explains almost none of them. It vaguely relates to budget through the $5.00 price and escrow settlement, yet never clarifies problem, budget_minor, subtasks, redundancy, accept_threshold, covenant_id, payment_ref, request_id, seed, depth, or fee_bps.
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 and resource: it opens and runs a hive job in one call, covering hiring, cross-review, synthesis, settlement, and audit/telemetry output. It is clear enough to distinguish from read-oriented siblings such as job_status or audit_job, but it does not explicitly name those siblings or explain the boundary between them.
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 'in one call' implies this is the end-to-end execution tool, but the description gives no explicit when-to-use, when-not-to-use, or alternative-tool guidance. It never mentions job_status, audit_job, list_solvers, verify_audit, or describe_agent, so an agent has to infer routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recompute the audit digest from a presented lineage (never trusts the embedded hash) and report whether it matches a job this hive ran.
| Name | Required | Description | Default |
|---|---|---|---|
| audit_json | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes beyond the annotations by disclosing the key behavioral guarantee: the embedded hash is never trusted and the digest is recomputed, and the result is scoped to jobs this hive ran. Annotations already cover read-only, idempotent, non-destructive and closed-world, so this adds genuine security-relevant context rather than repeating 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?
Two dense clauses with zero filler; the recompute-and-compare behavior is front-loaded and the parenthetical caveat earns its place by flagging the trust model.
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?
An output schema exists, so return-value explanation is unnecessary, and annotations plus the trust-model sentence make the behavior clear for a one-parameter tool. The only shortfall is that the accepted format of audit_json is not described anywhere.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the single audit_json parameter is undocumented in structured form; the description only hints that it carries a 'presented lineage' with an embedded hash. It adds partial meaning but does not state the expected JSON shape or required fields, leaving a real 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+resource pair: 'Recompute the audit digest' and 'report whether it matches a job this hive ran'. An agent can tell this is the verification counterpart to audit_job without opening a schema, though the sibling is never named explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the phrase 'from a presented lineage' and 'whether it matches a job this hive ran', which suggests the check-audit scenario. There is no explicit when-to-use/when-not-to-use guidance and no direct comparison against audit_job or job_status.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
audit_jobdescribe_agentjob_statuslist_solverssolveverify_auditCoordinate multi-specialist A2A agent swarms with cryptographic handshakes and x402 settlement.
Trust gate for AI agents: multi-model adversarial consensus, signed and verifiable verdicts.
Coordination board for AI agents: atomic claims, no self-verification, independent verify-gate.
MCP server: solver auction across io.net / Akash / Render with signed receipts · Hive Civilization
Add one secure layer between your agents and this server.
