blindoracle

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

With no annotations, the description carries the behavioral burden. It discloses that this is a report-producing check, that the report is signed, and that each call costs $0.25 USDC. It does not overpromise mutations or side effects.

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 conveys the trigger condition, report contents, output form, and pricing. 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?

Given a one-parameter schema and no output schema, the definition supplies the essential call context: purpose, contents, signed report, and cost. The parameter remains somewhat open-ended, but the tool is simple enough that the description is not incomplete.

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

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

The input schema already describes the single 'task' parameter at 100% coverage, so the description does not need to re-explain it. The description adds the agent-check framing, but not detailed instructions on formatting the task text; baseline 3 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 identifies a specific operation—pre-hire due-diligence on an agent—and states the decision context (before granting real spend authority). It differentiates itself from generic due-diligence/vetting siblings by naming agent-specific contents: settlement history, dispute rate, and flagged incidents.

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 'before you delegate it real spend authority' gives an explicit condition for use. It does not name sibling tools or spell out when not to use it, so it stops short of full routing guidance.

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

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

With no annotations, the description carries the full burden, and it discloses important behavior: an agent with no history returns an honest zero and badge 'none', never a synthetic score, plus the exact per-call cost. It does not cover auth, rate limits, or response shape, but the key honesty guarantee is well communicated.

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

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

Two sentences, front-loaded with the core purpose, with no filler. The parenthetical pricing detail earns its place since cost is decision-relevant for an agent.

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

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

The tool is simple and the schema is minimal, but the description does not bridge the gap between 'an agent's history' and the sole free-text 'task' parameter, so an agent may not know what to pass. There is also no output schema, so a short note on the returned badge value would have made this more complete.

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

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

The schema covers the single 'task' parameter at 100%, so the baseline is 3. The description adds no new meaning to that parameter and does not explain how the target agent is identified within the free-text task, leaving some 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?

The description clearly states what the tool does: it returns a queryable trust badge summarizing an agent's verified settlement history and frames it as the pre-first-transaction check. It does not explicitly differentiate itself from overlapping siblings like reputation.lookup or trust.receipt-verify, so it stops just 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 description gives an explicit usage context: check this before a first transaction as the minimum-viable signal. It does not state when not to use it or name alternatives, but the situational guidance is concrete and actionable.

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

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

With no annotations, the description assumes full disclosure burden and delivers richly: it reveals the adjudicator is the BlindOracle operator panel, the verdict is unilateral with no buyer contest channel, it is evidence-retained but not a disinterested referee, the live dispute_disclosure block is authoritative, there is no charge when the source cannot be fetched, and pricing is $5.00 USDC per call (x402). These are exactly the caveats an agent needs before invoking.

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?

Purpose is front-loaded and every sentence carries real information (verdict types, adjudicator identity, pricing, refund condition). It is dense rather than padded, though the long disclosure run-on could be trimmed slightly for readability.

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-style tool with no annotations and no output schema, the description covers outcome, ledger side-effect, adjudicator identity, and billing, which is substantial. The one gap is procedural: both sides 'submit evidence' yet the schema exposes only a single 'task' parameter, and neither description nor schema explains how evidence is supplied.

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?

Only one parameter ('task') exists and schema description coverage is 100%, so the baseline is 3. The description adds no syntax, format, or content guidance for the parameter, leaving the schema to carry it.

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 and resource ('Adjudication of a contested deliverable') and specifies the output artifact (signed verdict – upheld/overturned/withdrawn, ProofOfAdjudicatedOutcome 30129) written to a settlement ledger. It is a clear, distinctive purpose that no sibling tool plausibly duplicates, though it never explicitly routes against contenders like procurement.council or deliberation.multi-agent-debate.

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 scenario is implied (a contested deliverable where both sides submit evidence), which anchors when the tool applies, but there is no explicit when-to-use/when-not guidance and no named alternative for adjacent dispute or deliberation needs. Usage is inferable rather than stated.

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

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

With no annotations, the description bears the full burden. It discloses the single-use nature, the proof claims (specific deliverable, agent, time, immutability), and the cost per call ($0.05 USDC). It does not mention side effects such as whether the seal is stored or any network dependencies, but the provided details cover key operational facts. The absence of a return-format description is minor given the intended use as a receipt.

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, dense sentence that front-loads the core purpose ('A single-use cryptographic seal...') and appends the pricing as a parenthetical. Every element serves a function, with no filler or redundancy.

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

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

For a one-parameter tool with no output schema and no annotations, the description covers the purpose, cost, and the single-use constraint. It lacks details on how to construct the 'task' parameter or what the response format looks like, but these are not essential for a basic agent to invoke it correctly. The tool is simple enough that the description is largely adequate.

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

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

The schema describes the only parameter 'task' as 'Task/query text for this SKU,' which is 100% coverage. The tool description mentions 'specific deliverable' and 'specific agent' but does not explain how these map to the 'task' parameter. The description adds negligible value beyond the schema's own documentation, so the baseline of 3 is appropriate.

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

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

The description states a specific verb and resource: 'A single-use cryptographic seal proving a specific deliverable was produced by a specific agent at a specific time and has not been altered since.' This clearly distinguishes it from siblings like trust.receipt-verify (which verifies seals) and security.audit-attestation (which likely audits attestations). The term 'single-use' adds a distinguishing qualifier.

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

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

The description implies the tool is for creating a receipt that a counterparty can independently check, suggesting it is used when one needs to prove a deliverable's provenance and integrity to a counterparty. It does not explicitly state exclusions or alternatives, but the phrase 'the receipt a counterparty can independently check' gives clear usage context. A more explicit note about using trust.receipt-verify for verification would elevate the score.

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

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: timestamp-cited output format [n @ mm:ss], refusal with no charge when a transcript cannot be fetched, and pricing ($0.03 USDC via x402). It omits any latency, rate-limit, or auth detail beyond pricing.

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 refusal rule is stated twice in nearly identical, partly garbled form ('If no transcript can be fetched, the job is refused and you are not charged. Refuses, with no charge, when fetched transcript cannot be fetched.'), which bloats the definition without adding 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 single-parameter tool with no output schema and no annotations, the description covers input modes, output shape, failure semantics, and cost. The only real gap is the mismatch between the mentioned `urls` input and the actual schema.

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

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

Schema coverage is 100% for the single 'task' parameter, so baseline is 3. The description adds the notion of passing video URLs, but references a `urls` parameter that does not exist in the schema, which creates mild ambiguity about how URLs are actually supplied.

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 ('Researches YouTube videos from their real transcripts') and describes the two input modes clearly. The emphasis on real transcripts distinguishes it from sibling research tools like research.topic-deep-researcher and research.topic-news-scanner.

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?

Gives clear context for both invocation paths (pass video URLs, or describe a topic and it finds relevant videos) and states the refusal condition. It does not, however, name any sibling alternative or when to prefer a different research 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 are provided, so the description carries the full behavioral burden and does so well: it discloses live-vs-cached data, a DEGRADED first-line notice when live data is unavailable, settlement proof artifact, and per-call cost (x402 $0.02 USDC). It does not cover auth requirements or rate limits, but the freshness, failure-mode, and cost disclosures are meaningful.

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?

Front-loaded with the core capability, then supporting details (provenance, sibling positioning, degradation behavior, cost). It is dense but each clause adds operational value; slightly compressed for easy scanning.

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 and no annotations, the description must carry everything, and it covers data source, freshness, failure mode, cost, and sibling positioning. The one gap is return-shape/pagination expectations, but for a single-param analysis tool it is largely 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 100% and there is a single optional 'task' parameter, so the baseline is 3. The description adds no syntax or format guidance for the 'task' field, leaving the schema to do all the work.

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 concrete resource and scope: 'Real-time market data, technical indicators, and sentiment for any ticker,' a specific verb-free but resource-explicit purpose. It actively differentiates from siblings by positioning itself as a 'Broader single-ticker view than any one oracle.* SKU,' so an agent can distinguish it from oracle.price-feed, oracle.sentiment-analysis, etc.

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 clear context: use this for a broad single-ticker view that exceeds any individual oracle.* SKU, and notes it feeds crypto.investment-plays' risk scoring. It stops short of explicitly stating when NOT to use it or naming the exact alternative to pick instead for a narrower need, so it is strong but not fully routing.

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

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

With no annotations, the description carries the transparency burden. It discloses meaningful constraints: public records only, the BlindOracle trust envelope, and the $0.10 USDC per-call cost. However, it does not clarify whether the operation is strictly read-only, what the response contains, or how failures are handled.

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 entire description is two compact sentences plus a cost note; every element is informative and there is no filler. The source scope and trust wrapper are 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?

For a tool with no output schema and only one free-text parameter, the description should specify the expected payload format (especially how the URL is expressed in the task) and what result is returned. It leaves the most important operational detail ambiguous, so despite its clarity it is not complete enough for unambiguous invocation.

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 documents the single 'task' parameter as opaque query text (100% coverage), and the description adds that the task concerns a buyer-supplied public records URL, which clarifies what content belongs in the task string. This goes beyond the schema's generic label.

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 operation (public business-registry record extraction) with explicit sources (SEC, state Secretary of State, UK Companies House) and a distinguishing mechanism (buyer-supplied URL, BlindOracle envelope). This clearly differentiates it from siblings like data.sec-edgar-filing and data.web-extract.

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

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

The description implies the tool is for extracting registry records from a buyer-provided public URL, but it never explicitly states when to prefer it over similar tools like data.sec-edgar-filing or data.web-extract, and provides no when-not-to-use guidance. The context is helpful but largely implicit.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It does reveal key aspects: it is a read-only retrieval, includes a tamper-evident trust envelope (content hash, content-trap scan, provenance), and costs $0.05 per call. However, it does not describe the response format, error behavior, rate limits, or any side effects. This leaves significant gaps for a tool with 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?

The description is a single sentence with compact parenthetical details (forms, trust envelope, cost). It front-loads the primary purpose and avoids redundant phrasing or filler. Every piece of information earns its place, making it highly 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?

Given a single parameter and no output schema, the description covers the essential usage (what to retrieve and that there is a cost) but omits critical details such as the response format, pagination, or how the trust envelope is delivered. It does not explicitly state that the task parameter should contain the ticker or CIK, though it is implied. The description is adequate but not fully self-sufficient.

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

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

The schema parameter 'task' has a generic description ('Task/query text for this SKU') that does not explain how to specify the ticker or CIK. The tool description adds context by stating the purpose (ticker or CIK) but does not clarify the expected format of the task query (e.g., 'AAPL' vs '0000320193'). With 100% schema coverage but minimal parameter detail, the description adds some value but fails to fully compensate for the lack of parameter guidance.

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

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

The description clearly states the tool retrieves recent SEC EDGAR filings (10-K/10-Q/8-K) for a ticker or CIK. The verb 'retrieval' and specific resource make the purpose unambiguous, and it is distinct from sibling tools like data.business-registry or oracle.price-feed. The mention of the trust envelope and public-domain source adds helpful context without obscuring the core function.

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 for SEC EDGAR filings but does not explicitly state when to use this tool versus alternatives. It mentions the target audience (ticker/CIK) and the forms covered, but there is no mention of exclusions (e.g., 'use for non-SEC data use data.business-registry') or explicit conditions. The guidance is implied rather than explicit, so it falls short of a 4.

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

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

With no annotations, the description must carry the transparency burden. It discloses it is thin, holds no data inventory, and includes pricing and the BlindOracle envelope. However, it omits side effects, rate limits, error behavior, and introduces a URL concept that conflicts with the 'task' schema, creating confusion.

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

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

Two sentences, front-loaded with the core purpose, and includes essential operational details (Firecrawl, trust envelope, pricing) without any fluff. Efficient and well-structured.

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

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

With a single vague 'task' parameter and no output schema, the description does not clarify how to supply the URL or what output to expect. The disconnect between description and schema makes correct invocation impossible without external context.

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

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

Schema coverage is 100% for the single 'task' parameter, so baseline is 3. But the description mentions a 'buyer-supplied URL' that is not reflected in the schema, leaving unclear whether 'task' should contain a URL or a query text. This actively undermines parameter semantics.

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 ('extraction of main content') on a specific resource (a single buyer-supplied URL) using Firecrawl, and notes it is a thin tool with no data inventory. This clearly distinguishes it from research-heavy siblings like research.topic-deep-researcher.

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 is given on when to use this tool versus alternatives. It does not mention exclusions or comparisons to sibling tools, leaving the agent to infer usage from the generic extraction purpose.

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

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

With no annotations, the description carries the full burden. It usefully discloses panel size, model count, voting/forced-decision behavior, a degraded-output notice, and per-call cost ($2.00 USDC via x402), which is genuinely valuable. It omits latency, auth requirements, and what a successful result actually contains, so it is above minimal but not rich.

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 compact, and putting cost in parentheses at the end is sensible. But the sentence 'forced decision-making May deliver with a first-line DEGRADED notice...' is a run-on with a stray capital and garbled phrasing, which hurts readability. Front-loading the capability itself is good.

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 deliberation tool with no annotations and no output schema, the description covers capability, cost, and a degraded-output caveat, which is reasonable. It still lacks return-shape expectations and any guidance on when to prefer this over the many sibling council/oracle tools, leaving real gaps.

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 ('task') with 100% schema description coverage, so the schema already documents it. The description adds no syntax, format, or length guidance for the task text beyond what the schema provides, which lands at the baseline for high coverage.

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

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

The description names a concrete capability: a 5-11 agent panel debate using 11 LLM models with structured voting and forced decision-making. That is a clear verb+resource an agent can recognize. However, it does not distinguish this tool from plausible siblings like procurement.council, arbitration.dispute-settlement, or research.topic-deep-researcher, 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 explicit when-to-use, when-not-to-use, or named alternative. The only operational note ('DEGRADED notice when buyer question is unavailable') describes an output condition, not a selection criterion. An agent is left to infer that this is the multi-agent deliberation option among many council/oracle siblings.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It states that the tool 'surfaces cost overruns or scope creep,' which gives some idea of the output, but it doesn't specify the format, whether it's read-only, or any side effects. It's not misleading, but it's thin on behavioral detail beyond the core action.

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, focused sentence that front-loads the core purpose, followed by a pricing note. Every word earns its place, and there is no fluff or repetition of schema details.

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 single-parameter tool with no output schema, the description adequately explains what the tool does and what it surfaces. It could go further by describing the output format (e.g., a report or flag) or any prerequisites, but given the low complexity, it's nearly complete.

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

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

The schema has 100% coverage for the single 'task' parameter, and the description does not add any parameter-specific meaning beyond what the schema provides. Per the rubric, a baseline of 3 is appropriate when the schema fully documents parameters and the description doesn't need to compensate.

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 clear verb ('audit') and a specific resource ('an agent's actual token spend against its budget and declared task scope'), and distinguishes it from siblings by describing a unique finops/audit function that no other sibling covers. It's unambiguous what this tool does.

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: it's for independent auditing of token spend, but it doesn't explicitly state when to use it vs alternatives. Since no sibling offers a similar capability, the lack of explicit exclusions is acceptable, but the description doesn't provide context like 'use when a counterparty requests spend verification.' It's implied rather than stated.

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

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

With no annotations, the description carries the full behavioral burden. 'Check ... health and API status' conveys a read-only status operation, but it does not disclose response format, failure behavior, auth needs, or any side effects. This is minimally transparent.

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 states the target service and the two aspects checked. There is no filler or duplication of schema/annotation fields.

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 health check, the description names the service and the nature of the check, which is close to sufficient. It does not spell out the return payload, but the absence of an output schema and the low complexity reduce the need for more detail.

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 and the input schema already covers everything at 100%, so the 0-param baseline of 4 applies. The description adds no parameter meaning, but none is 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 uses a specific verb and resource: 'Check BlindOracle service health and API status,' making the operation clear. It does not explicitly contrast itself with sibling tools, but no sibling is obviously a health check, so the purpose is still distinguishable.

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 tool versus alternatives such as prediction.blindoracle or oracle.comprehensive-report. The description implies a status query, but it gives no prerequisites, no exclusions, and no context about operational conditions.

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

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

With no annotations, the description carries full burden; it does disclose two meaningful behaviors: a no-charge refusal path when the required sources cannot be fetched, and a $1.00 USDC per-call x402 cost. It omits permissions, latency, and output shape. Useful but partial 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?

The coverage list is well front-loaded, but the refusal clause is stated twice in near-identical wording ('Refuses, with no charge, when ≥5 web sources + registry/EDGAR lookups cannot be fetched' vs 'Refuses, with no charge, when the required source...cannot be fetched'). That redundancy wastes space, though the overall length remains short.

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?

No output schema and no annotations, so the description must carry the load. It names the scanned categories and the payment/refusal mechanics, which is helpful, but never describes what a successful scan returns or its structure. Adequate for a one-parameter tool, but leaves the return-value picture undefined.

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?

Only one parameter ('task') with 100% schema description coverage, so the schema already documents it. The description adds no syntax, format, or content guidance for the task string beyond what the schema says. Baseline 3 is appropriate.

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

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

States a specific verb+resource (automated due-diligence scan) and enumerates the coverage areas: financials, litigation, key personnel, IP, media sentiment, red flags. An agent can tell it is a broad DD scan rather than a single-source lookup like data.business-registry or data.sec-edgar-filing. It stops short of explicitly naming a sibling to contrast against, so it is clear but not maximally differentiated.

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 states refusal conditions and price but gives no guidance on when to choose this tool over the many adjacent siblings (data.business-registry, reputation.lookup, procurement.vendor-vetting, research.topic-deep-researcher). There is no when-to-use, when-not-to-use, or alternative routing. Implied only.

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

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

With no annotations, the description must carry the transparency burden. It discloses the deterministic HEAD/GET method, the PASS/FAIL output, and the $0.01 USDC per-call cost. However, it does not mention auth requirements, error handling, rate limits beyond cost, or whether it follows redirects.

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 core behavior is front-loaded in one dense sentence, followed by a business context code and cost. The SKU identifier is noise for an AI agent, but it is brief and does not undermine clarity. No superfluous filler.

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

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

For a tool with no annotations, no output schema, and only a single vague parameter, the description omits critical details: what constitutes a valid task, output formatting, failure behavior, and whether the parameter is truly optional. The agent is left to guess how to construct input and interpret the verdict response.

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

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

The schema only says the 'task' is 'Task/query text for this SKU', which is vague. The description adds that the task contains URLs, but does not specify their format (e.g., newline-separated, list, URL array) or whether an empty task is allowed, leaving ambiguity for a single required-ish parameter.

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 ('check'), a specific resource ('every URL in the task'), and a specific output ('PASS/FAIL verdict with per-URL status codes'). It is distinct from sibling tools like data.web-extract or ops.due-diligence-scan, which do not cover link integrity checking.

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 'Post-deploy verification SKU' provides an implicit usage context, but no alternatives, exclusions, or concrete when-to-use guidance are given. An agent is not told why to select this over other verification or scanning tools.

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

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

With no annotations, the description carries the full burden and does substantial work: it enumerates the return states, discloses the settlement proof mechanism and file, names its upstream dependencies, and specifies failure behavior (refusal with no charge). Missing only auth/permission requirements and any rate-limit detail, so not quite a 5.

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?

Front-loads the core verb+resource and return states in the first clause. The subsequent sentences each carry distinct information (proof, dependencies, failure, price), though the SKU/x402 jargon makes it denser than ideal.

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 or annotations, the description compensates well by describing return states, cost, failure semantics, and dependencies. It is nearly complete for a single-param tool, lacking only explicit permission/authentication context.

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

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

Single parameter with 100% schema description coverage, so the schema already documents it and the baseline is 3. The description adds no syntax or format guidance for the 'task' field beyond what the schema provides.

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

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

States a specific verb and resource ('Defines a custom price/event alert') and what it returns ('current trigger state — armed, fired, or stale'). Explicitly differentiates itself from siblings by declaring it is 'the trigger layer, not the data layer' and naming oracle.volatility-monitor and oracle.price-feed as its inputs.

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?

Gives clear context for when this layer applies versus the data-layer siblings it reads from, and states a concrete exclusion rule ('Refuses, with no charge, when live price + buyer threshold fields cannot be fetched'). It stops short of an explicit 'prefer X over Y' routing statement, but the trigger-vs-data distinction gives solid guidance.

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

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

With no annotations, the description carries the full burden and does so well: it discloses the executing agent (crypto-market-agent-sonnet), that every delivery settles with an HMAC-signed ProofOfSettledOutcome, that it may return a first-line DEGRADED notice when live data is unavailable, and that it is paid via x402 ($0.20 USDC per call). This is substantial behavioral context covering cost, failure mode, and settlement. It does not describe rate limits or the report's actual output format, keeping it short of a 5.

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?

Front-loaded with the core purpose, then scope, then proof/settlement and degradation behavior. Every sentence carries information, though the settlement/proof clause is dense and could be tightened. Appropriately sized for a multi-faceted 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 one-parameter tool with no output schema, the description covers purpose, scope, cost, degradation behavior, and delivery proof. The only minor gap is the absence of any detail on what the report body contains or how the combined reads are presented, but the essential call-time information is present.

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?

Only one parameter (task), and schema description coverage is 100%, so the schema already documents it. The description adds no syntax, format, or interpretation guidance for the task string beyond what the schema provides. Baseline 3 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?

States a specific deliverable (consolidated market/asset report combining price, volatility, sentiment, and arbitrage) for a specific scope (one ticker across venues). It explicitly positions itself against siblings: 'Broader scope than any single oracle.* SKU below; narrower and cheaper than security.massat-audit's compliance-grade evidence.' An agent can distinguish it from oracle.price-feed and the other oracle.* tools without opening schemas.

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 comparative positioning ('broader than any single oracle.* SKU', 'narrower and cheaper than security.massat-audit') tells the agent when this is the right choice versus its closest alternatives. It stops short of explicit when-not/if-then routing, but the scope boundaries are clear enough to select correctly.

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

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

With no annotations, the description carries the full behavioral burden and delivers: it discloses the refusal condition (live price feed or ≥2 chains unavailable), that refusals incur no charge, the settlement-proof artifact (ProofOfSettledOutcome, kind 30120), and per-call pricing. Only the return/payload shape is left unstated.

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?

Front-loaded with the core purpose, then layered with the sibling comparison, proof artifact, and refusal/pricing terms. Dense but each clause earns its place; the parenthetical pricing and proof-path details are slightly heavy but relevant.

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-param oracle read with no output schema and no annotations, the description covers purpose, refusal semantics, cost, and settlement proof—enough for correct invocation. The main remaining gap is the shape of the returned comparison, which it does not sketch.

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 'task' parameter is fully documented in the schema (100% coverage), so the schema already does the work. The description adds no syntax or format guidance for the task text beyond what is structured, making the baseline 3 appropriate.

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

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

States a specific verb (aggregates) and resource (token's price across chains/venues) with the added behavior of flagging the highest-deviation pair. It explicitly distinguishes itself from oracle.comprehensive-report and positions itself relative to oracle.market-arbitrage, so an agent can tell it apart from siblings without opening a schema.

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?

Names oracle.comprehensive-report as the broader alternative ('single metric, not a full report') and notes it feeds oracle.market-arbitrage's spread detection, giving clear usage context. It stops short of an explicit 'use this when X, use sibling when Y' statement, so it lands just below the top tier.

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 burden and does well: it discloses the failure mode (refuses, with no charge, when >=30d history cannot be fetched), the pricing model ($0.08 USDC per call via x402), and the settlement-proof artifact. It does not cover latency, rate limits, or the exact shape of the returned pattern 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?

Three dense sentences, front-loaded with the core purpose before routing and failure/cost details. Every clause carries information, though the parenthetical settlement-proof and pricing notes are stacked at the end rather than woven into the flow.

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 tool with no output schema and no annotations, the description covers purpose, routing, failure behavior, cost, and the settlement-proof output artifact, which is enough to call it correctly. Minor gaps remain around return format and latency, but these are secondary for this 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?

There is a single parameter ('task') with 100% schema description coverage, so the schema already documents it. The description adds no syntax, format, or content guidance for the task string, which is the expected baseline-3 outcome when the schema does the heavy lifting.

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 (historical trend/pattern analysis for an asset or time series) and explicitly differentiates its output from a generic up/down label. It also names the sibling it is not (oracle.volatility-monitor) and its downstream consumer (crypto.investment-plays), so an agent can place it precisely.

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?

Gives clear selection context: historical (not real-time) analysis, feeding crypto.investment-plays entry/exit logic, and the explicit refusal condition (price history >=30d unavailable). It names one alternative (oracle.volatility-monitor) but does not survey other oracle siblings an agent might confuse it with.

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

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

With no annotations, the description carries the full burden and does so well: it discloses a refusal condition ('Refuses, with no charge, when live prices from ≥2 venues cannot be fetched'), a pricing model (x402 $0.10 USDC per call), a settlement-proof artifact, and an upstream dependency. It stops short of describing return structure, latency, or auth requirements, keeping it at 4.

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?

Purpose is front-loaded in the first clause, with supporting facts (dependency, proof, pairing, refusal, price) following in descending importance. Slightly dense with implementation details like the kind number and file path, but no sentence 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?

Given no output schema and no annotations, the description supplies the safety/cost/refusal profile an agent needs before invoking it. It lacks detail on what the returned entry/exit spread looks like, but the essential behavioral contract is present.

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 'task' parameter with 100% schema description coverage, so the schema already documents it and the baseline is 3. The description adds no format, example, or content expectations for the task string, so it does not exceed baseline.

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

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

States a specific verb+resource ('Detects live cross-venue arbitrage spreads for a given asset') and explicitly clarifies the deliverable is an 'actionable entry/exit spread, not just a price delta'. It also distances itself from its nearest sibling by noting it is built on oracle.cross-chain-prices, so an agent can distinguish the two without reading either schema.

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?

Gives clear context for use by naming companion tools (crypto.investment-plays for a 'full execution plan') and the dependency on oracle.cross-chain-prices. It does not, however, state an explicit when-not or directly compare itself against alternatives like oracle.price-feed or oracle.volatility-monitor, so guidance is strong but not exhaustive.

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 load, and it delivers real behavioral context: per-read source citation rather than a black-box number, a settlement proof artifact, a no-charge refusal when the live feed is unavailable, and x402 pricing of $0.02 USDC per call. The one weakness is that the refusal sentence is duplicated verbatim, diluting otherwise solid disclosure.

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

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

Purpose and pricing are reasonably front-loaded, but the description wastes space: 'Refuses, with no charge, when live price feed cannot be fetched' and 'Refuses, with no charge, when the required source (live price feed) cannot be fetched' say the same thing twice. Removing the duplicate would tighten an otherwise acceptable block.

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 single-parameter tool with no output schema and no annotations, the description covers the essentials an agent needs: what it returns, how it prices and bills, that it cites sources, and that it refuses without charge when the feed fails. The missing piece is the shape/format of the 'task' input, but overall it is complete enough to call correctly.

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

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

Schema coverage is 100% and there is only one freeform 'task' parameter, so the schema already documents the input; baseline is 3. The description does hint that the task should carry a 'named pair and venue,' which adds a little semantic direction, but it never explains the expected format of the 'task' string.

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: 'Real-time price feed for a named pair and venue, with the source cited per read.' It also positions itself relative to siblings by calling out that it is 'the base data layer the other oracle.* SKUs (arbitrage, volatility, alerts) are built on.' Clear and distinguishable, though the claim of 'named pair and venue' inputs does not map cleanly to the single 'task' param.

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?

It implies usage by naming itself as the foundation for oracle.arbitrage, oracle.volatility and oracle.alerts, which helps an agent infer routing. However, there is no explicit when-to-use/when-not statement nor a named alternative to select against, so guidance remains implicit.

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

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

With no annotations, the description carries the full burden, and it does disclose non-obvious behavior: a possible first-line DEGRADED notice when live data is unavailable, a settlement proof artifact (ProofOfSettledOutcome, kind 30120), the shared methodology, and an x402 price of $0.06 USDC per call. It stops short of describing auth requirements or the shape of the scored output, so 4 rather than 5.

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?

Front-loads the core promise ('Social + news sentiment read...') before proof/pricing housekeeping. It is dense with four distinct clauses, but each earns its place by covering methodology, provenance, degradation, and cost; slightly compressed but not 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 tool with no annotations and no output schema, the description supplies the essentials an agent needs: what it returns conceptually (scored, sourced sentiment), its sibling relationship, its degraded-mode behavior, and its cost. The main residual gap is the exact return shape, but the 'scored and sourced' phrasing is a reasonable stand-in.

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

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

Schema coverage is 100% for the single 'task' parameter, so the baseline is 3. The description adds no syntax, format, or example guidance for what belongs in the task string beyond the phrase 'named crypto asset or topic,' which is already implied.

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 ('sentiment read for a named crypto asset or topic, scored and sourced') and explicitly disambiguates from a sibling by noting it uses the same methodology as research.topic-sentiment-analyzer but is 'scoped to crypto assets instead of general topics.' An agent can pick it apart from research.topic-news-scanner and research.topic-sentiment-analyzer without opening a schema.

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 rule versus research.topic-sentiment-analyzer ('crypto assets instead of general topics') gives a clear selection criterion. It also flags that output may arrive with a DEGRADED notice, implying the call still succeeds when live data is thin. There is no explicit when-not-to-use or prerequisite statement, so it falls short of a 5.

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

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

With no annotations the description carries the full burden, and it does disclose important behavioral traits: refusal with no charge when the live price-history source is unavailable, plus a concrete price point (x402: $0.04 USDC per call) and a settlement proof artifact (kind 30120). Return format, latency, and rate limits remain undisclosed.

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 purpose is front-loaded and the sibling routing is efficient, but the refusal condition is stated twice in near-identical sentences ('when live price history cannot be fetched' / 'when the required source (live price history) cannot be fetched'), which is wasted space and reads as an editing artifact.

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 single-parameter tool with no annotations and no output schema, the description covers purpose, alternatives, failure/pricing behavior, and a settlement-proof reference. It stops short of describing what the volatility read actually returns, which is the one remaining 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 coverage is 100% for the single 'task' parameter, so the baseline is 3. The description adds no meaning to that parameter, and its mention of 'configurable alert thresholds' is not represented in the schema, so it does not enrich parameter understanding.

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 ('Real-time volatility read for a trading pair') and explicitly differentiates from two siblings: alert-generator 'fires the alert' and historical-analysis 'explains the trend behind the number.' An agent can select this tool without opening any schema.

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?

Names two alternatives with the role each plays, which gives clear context for choosing this tool. It does not, however, address other plausible siblings like oracle.price-feed or crypto.market-analyzer, and gives no exclusions for 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 burden of behavioral disclosure. It exceeds that burden: it discloses the retirement status, the price of 0.00, the fact that no payment can settle, and the historical bug where the previous $0.01 price caused a charge-then-refund cycle. This is exemplary transparency about a defective tool.

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?

Front-loaded with 'RETIRED' and efficient overall, but somewhat verbose with the RQ code, exact date, and detailed historical bug narrative. Every sentence does earn its place for a retired tool — the charge-then-refund explanation is important context — though it could be tightened without losing meaning.

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?

Completely adequate for a retired tool: it states retirement, why it's unusable, what happens when called, and points to the decision document for details. No annotations or output schema exist, and the description fully compensates. Nothing an agent needs to avoid misusing this tool is missing.

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% — the single 'task' parameter is documented in the schema. The description adds no parameter-level detail, which is acceptable given full coverage. Baseline 3 is appropriate; the description's value lies in retirement disclosure, not parameter semantics.

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 leads with 'RETIRED' and immediately states what the tool cannot do: there is no market state to query because the underlying contract has zero markets. It names the specific verb-resource relationship (querying market state via prediction.oracle) and clearly differentiates itself from siblings by declaring itself non-functional. An agent can tell immediately this tool should not be selected.

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?

Explicitly states when not to use it: 'NO 402 challenge is issued and no payment can settle.' It explains the failure mode (charge-then-refund cycle) and references the decision document for rationale. This is stronger than typical guidance because it actively prevents misuse rather than merely describing intended use.

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

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

With no annotations, the description carries full burden and does well: it discloses the forced-vote mechanism, output contents (verdict, vote breakdown, ERC-8004 proof), a no-charge refusal policy tied to source-fetch failures, and per-call pricing ($2.00 USDC). The main gap is the absence of any latency/rate/side-effect detail beyond the paywall.

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?

Front-loaded with the core mechanism and output, which is good. However, the two refusal sentences are redundant paraphrases of the same condition, wasting space and slightly muddling whether they describe one or two distinct rules.

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 deliberation tool with no annotations and no output schema, the description covers output contents, refusal behavior, and cost well enough to call it correctly. The duplicated refusal clause and lack of timing/determinism context are minor omissions.

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

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

Schema coverage is 100% for the single 'task' parameter, so the schema already documents it. The description adds nothing about task format, length, or what constitutes a well-formed vendor subject, leaving the baseline 3.

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

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

States a specific action (multi-agent panel debate producing a forced vote) plus the resource (vendor decisions), and names the panel roles. An agent can distinguish it from procurement.vendor-vetting, though it overlaps conceptually with deliberation.multi-agent-debate, which is not addressed.

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?

'Forced vote on any vendor decision' implies the intended use case, and refusal conditions clarify boundary behavior. But there is no explicit when-to-use vs the sibling vendor/procurement tools or deliberation.multi-agent-debate, so routing 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?

With no annotations to fall back on, the description carries the full burden and does so very well: it states the data is 'signed', 'ledger-derived', 'read from the live ledgers', and 'never fabricated'. It also discloses the no-charge `insufficient_subject` error behavior and the $0.01 per-call cost, which is exactly the kind of behavioral context an agent 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?

The description is dense but efficient: purpose, field scope, data provenance, error behavior, exclusions, alternatives, and cost are all packed into three well-organized sentences. It is front-loaded with the core purpose and every sentence adds useful 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?

The description covers the tool's domain, data sources, error behavior, cost, and alternatives impressively. However, the lack of an output schema combined with the unresolved `subject` vs `task` parameter mismatch means an agent still cannot reliably construct a valid request. This is a noticeable completeness gap for a tool with no annotations.

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

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

The description instructs callers to pass the agent name or erc8004 id as `subject`, but the input schema only defines a `task` parameter. The `task` description is generic ('Task/query text for this SKU') and the description never explains that `task` must carry the subject value. This active mismatch between the described parameter and the actual schema makes the parameter semantics misleading.

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

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

The description clearly identifies a specific resource (trust evidence about a NAMED BlindOracle agent), a specific action (return signed, ledger-derived trust evidence), and enumerates the concrete fields returned. It also differentiates itself from the related external-company research tools by explicitly naming what it does not do.

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

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

The description gives an explicit when-not-to-use and alternative tools for external company research: 'It does NOT research external companies; use procurement.vendor-vetting or ops.due-diligence-scan for that.' However, it does not distinguish itself from other close sibling trust tools like agent.trust-badge or reputation.lookup, so guidance is good but not fully comprehensive.

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 the description carries the full burden and does so well: it discloses the output shape (0-10 score, per-category findings, red flags), the data-limitation ('does not retrieve filings, news, or breach databases' - it reasons only over supplied vendor details), the AI-generation disclosure + content hash, the refusal policy with no charge, and the x402 price. This is exactly the behavioral context an agent needs beyond a 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?

Front-loaded with purpose, then lenses, then output, then limitations, then alternative, then refusal and price. Dense but every sentence earns its place; the parenthetical x402 pricing at the end is slightly awkward placement but informative. Minor efficiency loss from stacking many clauses.

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 no annotations, no output schema, and a single trivial parameter schema, the description covers output shape, input requirements, limitations, disclosure/compliance, refusal behavior, pricing, and sibling routing. An agent has everything needed to decide whether and how 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?

Schema coverage is 100% for the single 'task' parameter, but the schema description is generic boilerplate ('Task/query text for this SKU'). The prose description partially compensates by explaining the reasoning basis ('vendor details you supply'), which hints at what the task text should contain, though it does not specify the input format for vendor details. Better than baseline 3 due to the input-content hint.

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

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

Specific verb+resource+scope ('structured vendor risk assessment across four lenses') and explicitly differentiates from sibling security.massat-audit by naming it and contrasting use cases. An agent can distinguish this from procurement.council, procurement.trust-layer, reputation.lookup without opening schemas.

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?

Explicit routing: 'For an automated audit of a live agent system, see security.massat-audit.' Also states the refusal condition (>=5 web sources unfetchable) and the pricing. When-to-use, when-to-use-alternative, and failure behavior are all disclosed.

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 bears full responsibility for behavioral disclosure. It reveals the read-only nature ('look up'), the data source (signed on-chain proofs, ensuring verifiability), and the cost ($0.01 USDC per call), which is valuable operational context. It does not mention failure modes, latency, or rate limits, but for a simple lookup tool these are minor omissions. No contradiction with annotations exists.

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

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

The description is two sentences, with the core purpose front-loaded and additional context (data source and cost) appended succinctly. There is no redundancy or filler. Every clause adds value, making it an exemplary model of concise, structured documentation.

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

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

The description covers the primary purpose, data source, and cost, and hints at the return content (jobs, disputes, trust-score trend). However, it omits crucial parameter guidance (the 'task' ambiguity) and any prerequisites or limitations (e.g., which chains or proof formats are supported). No output schema exists, so the description could better specify what the agent will receive. These gaps make it adequate but not fully complete.

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

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

The sole parameter 'task' is described in the schema as 'Task/query text for this SKU,' which is vague and does not align with the tool's purpose of looking up an agent's track record. The tool description does not clarify what should be passed (e.g., agent address, name, or ID). Even though schema coverage is 100%, the semantic meaning is ambiguous, and the description fails to compensate for this gap. The agent would struggle to know what value to supply.

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

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

The description clearly states the action ('look up') and resource ('an agent's settlement track record'), and enumerates the content (completed vs. failed jobs, dispute history, trust-score trend) plus the data source (signed on-chain proofs). It explicitly distinguishes from self-reported claims, which separates it from generic reputation tools. The verb and resource are specific, and the description differentiates from sibling trust tools by emphasizing on-chain verification.

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

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

The description gives an explicit usage context: 'before you transact with it,' which tells the agent when to invoke it. It also contrasts with self-reported claims, implying a reliability advantage. However, it does not explicitly name alternative tools or state when not to use it, despite several sibling tools (e.g., agent.trust-badge, procurement.vendor-vetting) serving similar trust-assessment purposes. A clear alternative reference would earn a 5.

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 present, the description carries the full burden and does so well: it discloses cost ($0.05 USDC x402), the refusal-without-charge behavior for ≥5 unfetchable sources, the '(unverified — no source)' marking policy, and the ProofOfSettledOutcome (kind 30120) settlement artifact. These are exactly the behavioral traits an agent needs before invoking a paid tool.

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?

Front-loaded with what the tool produces, then cost, then routing guidance. Dense but nearly every clause earns its place; the parenthetical settlement/x402 details add minor clutter for a single-tool 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?

No output schema exists, so the description correctly compensates by enumerating the return shape (exec summary, mechanisms, alternatives, risks, [n] citations) and the source-traceability rules. Combined with pricing and refusal semantics, an agent has everything needed to call and interpret 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?

Only one parameter exists and schema description coverage is 100%, so the schema already covers it. The description adds useful semantics about supplied `urls` (fetched, content-scanned, cited as numbered sources), but `urls` is not present in the declared input schema, creating a mild mismatch rather than enriched schema documentation.

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 product (structured research brief with exec summary, mechanisms, alternatives, risks, citations) over a specific mechanism (live web search + supplied URLs), and explicitly contrasts itself with research.topic-news-scanner and content.youtube-research. An agent can distinguish it from all nearby siblings without opening a schema.

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?

Explicitly names alternatives and the axis of differentiation: 'Deeper than research.topic-news-scanner; web + supplied documents vs content.youtube-research's video-only pool.' It also states a hard exclusion ('not a crawler: URLs not passed in `urls` are not opened') and a no-charge refusal condition, giving both when-to-use and when-not-to-use.

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

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

With no annotations, the description carries the full burden and largely succeeds: it discloses the paid model (x402, $0.02 USDC per call), the settlement proof artifact (ProofOfSettledOutcome, kind 30120), and the no-charge refusal condition when sources can't be fetched. It is docked for the duplicated, garbled refusal sentence rather than a single clear failure-mode statement.

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 opening is well front-loaded with the core capability and pricing, but the description repeats the same refusal rule twice in near-identical, awkwardly worded sentences ('Refuses, with no charge, when ≥3 fetched web sources cannot be fetched' vs. '...when the required source (≥3 fetched web sources) cannot be fetched'), which adds noise rather than 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 single-parameter tool with no output schema and no annotations, the description covers the important agent-facing facts: cost model, settlement artifact, failure/refund behavior, and tier positioning versus the deep researcher. What is missing is a mention of the shape/timing of returned items, but the core call-time decisions are covered.

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 a single 'task' parameter and schema description coverage is 100%, so the schema already documents it fully. The description adds no syntax, format, or constraint guidance for 'task' beyond what the schema provides, which is the baseline 3 case when the schema does the heavy lifting.

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 ('Fast real-time news scan across 44+ curated domains') and adds scope ('every item source-attributed'). It explicitly positions itself against a named sibling, research.topic-deep-researcher, as the 'quick-scan tier', so an agent can distinguish them without opening either schema.

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?

Names the alternative (research.topic-deep-researcher) and gives the selection criterion implicitly: this is the fast quick-scan, the other is the slower citation-grade report. That is a clear context signal, but there is no explicit 'use this when / avoid when' phrasing or list of prerequisites for choosing this tier.

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

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

With no annotations, the description carries the full behavioral burden and does well: it discloses the settlement proof mechanism (kind 30120), the failure/refund policy (refuses with no charge when fewer than 3 web sources can be fetched), and the per-call price (x402 $0.03 USDC). It does not describe latency, rate limits, or the shape of the scored result beyond 'per-channel'.

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 core purpose is front-loaded, which is good, but two consecutive sentences state essentially the same refusal condition with inconsistent phrasing ('>=3 fetched web sources cannot be fetched' vs 'the required source (>=3 fetched web sources) cannot be fetched'), which wastes space and muddies the rule.

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 single-parameter tool with no output schema, the description covers purpose, sibling differentiation, failure semantics, and cost. The main omission is any indication of the returned structure (per-channel scores, channels covered), which matters more since no output schema exists to compensate.

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% for the single 'task' parameter, so the schema already documents the input. The description adds no syntax, format, or constraint details for the task text beyond implying it is a topic name; baseline 3 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?

States a specific verb+resource (opinion/sentiment mapping) and a distinguishing scope (per-channel scoring across social, expert, and community channels for a named topic). It also explicitly separates itself from the sibling oracle.sentiment-analysis by topic domain, so an agent can route without opening either schema.

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?

Names the alternative (oracle.sentiment-analysis) and the condition that selects this tool (general topics rather than crypto assets), which is genuine routing guidance. However, it gives no guidance relative to the other research.* siblings (topic-news-scanner, topic-deep-researcher) and no explicit 'when not to use' beyond domain scoping.

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

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

With no annotations, the description carries the full burden. It clearly states the tool does not perform the audit, only attests that it was performed and findings match claims, which is a valuable behavioral disclosure. It also transparently mentions the cost per call ($0.50 USDC), adding context an agent would otherwise lack. However, it does not mention authentication, idempotency, or error behavior, but these are less critical for an attestation service.

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

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

The description is a single, well-structured sentence that front-loads the core purpose, followed by a parenthetical cost note. It is concise with no wasted words, though the cost information could be seen as extra but is useful for decision-making.

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, the description should explain what the agent receives back. It mentions 'the credential a checkpoint can trust' but does not specify the format, content, or any requirements for calling the tool. The parameter is vague, and there is no mention of prerequisites or error conditions, leaving some gaps for an agent to fully understand the call.

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% – the single parameter 'task' is described as 'Task/query text for this SKU'. The tool description does not add any further meaning about what 'task' should contain, leaving the schema's vague description as the only guidance. Baseline of 3 is appropriate since the schema covers the parameter, but no extra elaboration is provided.

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's function: neutral third-party notarization of an AI audit result, explicitly disclaiming that the tool itself runs the audit. It distinguishes itself from sibling tools like security.process-attestation or security.enterprise-audit by its unique role as an independent attestation service.

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 when a checkpoint needs to trust an audit result without re-running it, but it does not explicitly name alternatives or provide exclusion criteria. No sibling differentiation is given, so an agent must infer when to choose this over other security tools.

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

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

With no annotations, the description carries the transparency burden. It clearly discloses the verification behavior, the registry lookup, the credential conditions checked, and the per-call cost. It does not mention authorization requirements or side effects, but the read-only nature is strongly implied and the cost disclosure is valuable.

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 tight, informative sentence with a helpful cost parenthetical. Every word earns its place, and the key verification purpose is 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?

For a one-parameter tool with no output schema, the description is reasonably complete. The main gap is that it never explains what should go into the 'task' parameter, and it does not differentiate itself from other verification/attestation siblings beyond the specific Concordium card resource.

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

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

The schema description covers the single 'task' parameter completely, so the baseline is 3. The tool description adds no additional meaning about what the task text should contain or how it maps to the identity card being verified.

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 ('verifies') and a precise resource ('Concordium identity card integrity and badge status') against a specific authority ('issuing registry'), and states the confirmation outcome ('wasn't forged or revoked'). This clearly distinguishes it from generic sibling verification tools.

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

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

The phrase 'before you rely on it' provides a clear use context and timing for when this tool should be invoked. However, it does not explicitly name alternative tools or state when not to use it, which keeps it just below the top score.

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

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

With no annotations, the description carries the full burden and does reasonably well: it discloses the deliverable (signed ProofOfAuditReport, Merkle-anchored), the billing model ($25.00 USDC per call via x402), and a notable failure behavior (refuses with no charge when the source cannot be fetched). It does not cover auth requirements or latency, keeping it short of a 5.

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?

Dense but well front-loaded: the core deliverable leads, followed by the target scenario, the refusal behavior, and pricing in a parenthetical. Every clause carries information, though the phrasing is compressed enough to require a careful 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?

For a complex multi-agent paid audit with no output schema, the description covers the deliverable, the buyer scenario, the cost, and a failure mode. It could say more about what the report contains or how the audit is scoped, but what an agent needs to decide and call is largely present.

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?

One parameter with 100% schema description coverage, so the schema already documents 'task'. The description adds no syntax, format, or constraint detail about that parameter, so baseline 3 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?

States a specific verb and resource: a '13-agent coordinated security audit producing a signed ProofOfAuditReport, Merkle-anchored to Base.' The phrase 'not a self-attestation' distinguishes it from the attestation-style siblings, but it does not name specific siblings like security.audit-attestation or security.process-attestation, leaving some overlap ambiguity.

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?

Gives a target scenario ('enterprises that need documented evidence an agent fleet was assessed before deployment') which implies when to use it, but names no alternatives and provides no explicit when-not guidance beyond the fetch-failure refusal case.

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?

There are no annotations, so the description carries the full burden. It discloses that the tool is a test (not a compliance artifact) and includes the cost per call ($0.50 USDC), which is useful. However, it does not mention whether it is read-only, whether it actively sends payloads to the target, or what the response looks like.

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 one substantive sentence plus a parenthetical cost note. The core action and differentiation are front-loaded, and every part earns its place. No filler or redundancy.

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

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

For a simple one-parameter tool, the description gives enough to select and invoke it: the task text is parameterized and the cost is known. However, without an output schema or any mention of return format, an agent cannot predict how to interpret the result. This is a notable but minor gap.

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

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

Schema description coverage is 100% for the single 'task' parameter, so the schema already documents it. The tool description does not add any additional meaning or syntax guidance for that parameter, so no credit beyond the baseline is warranted.

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 ('Tests'), a concrete resource ('counterparty agent's input handling'), and narrows the scope to prompt-injection and content-trap patterns. It also differentiates itself from compliance-style checks, making it distinguishable from sibling security tools even without reading their schemas.

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 'a concrete resilience check, not a compliance checkbox' provides clear context and a when-not (don't use it for compliance). It does not explicitly name alternatives, but the intended use case is clear enough for an agent to select 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?

With no annotations, the description carries the burden and it discloses useful behavior: findings are Merkle-committed, the report is signed, and each call costs $5.00 USDC. However, it does not state the return format, whether the audit is read-only beyond the implication of an audit, or what happens if the audit process fails.

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

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

Two sentences plus one pricing parenthetical, all front-loaded and free of filler. It states the action, scope, context, output commitment, and cost efficiently.

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

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

The tool is a paid audit operation with no output schema and no annotations, yet the description does not specify the report's shape, verdict format, or how to interpret the signed/Merkle-committed evidence. It also leaves the relationship to several sibling security/audit tools unexplained.

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

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

Schema coverage is 100% and the single parameter 'task' already has a schema description ('Task/query text for this SKU'). The tool description adds no additional parameter meaning, so the baseline score of 3 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?

States a specific purpose: it performs an independent multi-agent security audit of a counterparty agent or MCP server, scoped to OWASP ASI01-ASI10, before granting access or spend authority. This is clear but does not explicitly contrast with sibling audit tools, so it narrowly misses the top score.

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 a clear trigger condition ('before you grant it tool access or spend authority'), which tells an agent when this audit is appropriate. It does not list exclusions or name alternatives such as security.enterprise-audit or security.massat-conformance, so it is not fully explicit.

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

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

With no annotations, the description carries the full burden. It discloses the core check-and-flag behavior and adds pricing information ($0.25 USDC per call), but it does not explicitly state read-only semantics, side effects, or failure behavior. This is adequate but leaves important behavioral details unspecified.

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

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

The description is two concise sentences: the first states the purpose, the second states the cost. There is no fluff, and the most important information is front-loaded. Every part 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?

Despite the simple one-parameter schema, the description is incomplete for an agent expecting to invoke the tool. There is no output schema and no description of what the tool returns (e.g., a boolean, a report, or errors), and no guidance on how this relates to sibling security tools. An agent would not know what to do with the result or when to choose this over alternatives.

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's description of 'task' is generic ('Task/query text for this SKU'), but the tool description adds meaning by clarifying that the task concerns a counterparty's stated security posture. This helps an agent infer what to put in the parameter, going beyond the placeholder schema text.

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 checks a counterparty agent's stated security posture against the MASSAT governance framework and flags invalid claims. It uses a specific verb and resource, and distinguishes itself from sibling tools like security.massat-audit by focusing on conformance of stated claims rather than a general audit.

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

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

No guidance is provided on when to use this tool versus alternatives such as security.massat-audit or security.enterprise-audit. There are no exclusions, prerequisites, or contextual hints beyond the general purpose, so an agent must infer usage from the purpose 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?

With no annotations, the description carries the full burden. It does disclose the signed nature of the attestation and the per-call cost, which is useful. Still, it doesn't describe side effects, authentication requirements, return format, or what the caller actually receives beyond 'signed attestation'.

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 and front-loaded with the core definition, followed by a brief use-case explanation and a cost note. Every sentence contributes useful information, and there is no redundant 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 single-parameter tool with no output schema and no annotations, the description provides the essential concept and a usage trigger, but it leaves gaps around what the task text should contain and what the returned signed attestation looks like. It is adequate but not fully self-sufficient.

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%, so the baseline is 3. The description doesn't add meaningful guidance about how to compose the 'task' parameter, and the schema's 'Task/query text for this SKU' is itself vague. The connection between 'task' and the described process-attestation behavior is only implicit.

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 that this tool produces a 'Signed attestation that a specific process was followed' and contrasts it with outcome-only attestations. It conveys the core purpose well, though it doesn't explicitly differentiate itself from closely related sibling tools such as security.audit-attestation.

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

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

The description gives a clear usage context: use it when a counterparty needs evidence of how something was done, not merely that it was done. However, it doesn't name alternative tools or state when not to use this one, so it lacks explicit exclusion 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It usefully discloses that verification occurs before introduction, that impersonation risk is mitigated, and that the call costs $0.01 USDC. Still, it does not describe what happens on failed verification, what the response contains, or whether the introduction persists.

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

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

Two sentences with no wasted words. The core behavior is front-loaded, the safety rationale follows, and the pricing note is concise and actionable. Everything included 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?

The description covers the essential purpose and a pricing detail, but the single 'task' parameter is underspecified, there is no output schema, and failure behavior is not described. An agent could invoke the tool but would be uncertain about how to format the task and what to expect in return.

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

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

Schema coverage is 100% and the sole parameter 'task' has a description, but that description is vague ('Task/query text for this SKU') and does not clarify how two agents are specified. The tool description adds no additional meaning about parameter format or expected content, so the baseline of 3 is appropriate.

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

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

The description states a specific verb ('introduces'), a resource ('two agents'), and a key condition (verified identity and delegation chain). It distinguishes the tool's core function from siblings like trust.receipt-verify or social tools by emphasizing verified peer-to-peer introduction, though it does not explicitly name any sibling 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 the use case: introduce two agents when counterparty authenticity matters, and the verification gate suggests when this tool is appropriate. However, it does not explicitly state when NOT to use it or mention any alternative tools that might be preferable in other scenarios.

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

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

With no annotations, the description carries the full behavioral disclosure burden Stan and does so richly: auto-direction detection, preservation of formatting/names/numbers, refusal of mainland-CN data subjects, and a trust envelope with content hash+scan+provenance. It even discloses cost at $0.05 USDC per call.

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 and front-loaded with the core purpose, followed by behavioral guarantees and constraints. Technical jargon like 'BO trust envelope' and 'x402' pack content efficiently but may require domain knowledge.

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

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

For a simple one-parameter tool with no output schema, the description covers purpose, direction auto-detection, formatting preservation, data-subject restrictions, deliverable provenance, and cost. The only minor gap is the lack of explicit output format, but translation output is strongly implied.

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 the single `task` parameter, yielding a baseline of 3. The description adds that the task involves documents/text, but it does not clarify whether `task` should contain raw content or a natural-language instruction. Adequate but not enhanced.

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 function: professional Simplified-Chinese<->English translation of documents and text. It is unambiguous, and with no translator siblings, it is clearly distinguishable from every other tool in the list.

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?

It clearly implies when to use the tool (whenever CN<->EN translation is needed) and explicitly signals a key exclusion: it refuses mainland-CN data subjects due to PIPL guarding. It does not name alternatives, but no translation alternatives exist among siblings, so the guidance is sufficient.

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

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

With no annotations, the description carries the full burden, and it delivers: it states deterministic execution, 'no LLM,' exact cryptographic operations, Base-payment confirmation, completeness in one call, and the $0.01 USDC x402 cost. This goes well beyond the structured schema.

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

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

The verification scope is front-loaded and every sentence adds information (checks, completeness, determinism, cost, free alternative). It is somewhat long and technical, but there is no real 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 cryptographic verification tool with no output schema and no annotations, the description should clarify what the agent must put in `task` and what the response looks like; both are missing. Otherwise, the operational details, cost, and determinism are well covered.

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

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

The schema has 100% description coverage for the only parameter, so the baseline is 3, but neither the schema text ('Task/query text for this SKU') nor the tool description explains how to supply a specific receipt/proof_id. The description adds detailed behavior but no parameter guidance, so it remains at baseline.

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

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

The description opens with a specific verb and resource, 'Verify a BlindOracle receipt,' and enumerates concrete checks that distinguish it from similar attestation/verification tools (append-only proof rail, payload hash, HMAC-SHA256, Base payment). This leaves no doubt about what the tool does.

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?

It gives a clear use context: buyers need the parts they 'cannot check alone,' and it explicitly points the self-checkable portion to a free published skill instead. It does not name sibling tools or explicitly list exclusions, so it is not a full 5.

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