CVIN

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

With no annotations provided, the description carries the full burden and does add real context: price ($10.00), payment rail (x402), and 30-day expiry. However, for a monetary, non-reversible purchase it omits critical behavior — whether the charge is refundable, how the x402 payment is authorized (wallet/signing requirements), and how the key is delivered back to the agent (response body vs. header).

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?

Effectively one dense sentence that front-loads the action, then the validity period, then the endpoint coverage, then price, then targeting. Every clause carries information; the only minor cost is that the parenthetical endpoint list and price parenthetical make it slightly crowded to scan.

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?

It covers what is bought, what it unlocks, how long it lasts, and what it costs — the essentials. But for a paid mutation tool with zero annotations and no output schema, an agent still cannot tell how payment is completed or where the resulting key appears, which is a meaningful completeness 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?

Only one optional parameter exists and the schema documents it fully (org name, ≤60 chars, recorded in key metadata), so the schema alone is sufficient and the description adds little. With a single optional param at 100% coverage, the description not repeating it is acceptable rather than a gap.

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

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

States a specific verb and resource (self-service purchase of a risk-subscription API key) plus concrete scope: 30-day validity, and access to the history / verify / watch / report endpoints. Because the sibling tools are those very endpoints (cvin_history, cvin_verify, etc.), explicitly naming what the key unlocks makes the distinction from siblings clear 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?

Gives a clear use condition — 'suitable for agents needing batch or high-frequency verification' — and implicitly contrasts it with the per-call payment model used elsewhere. It does not spell out a when-not condition (e.g. 'for one-off checks, call cvin_verify directly') or name a sibling explicitly, so it stops 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 must carry the full behavioral burden; it does disclose useful traits beyond structure — content is bilingual (中英双语), is paste-ready text rather than a link, and is royalty-free with no attribution required. It says nothing about whether id and kind are mutually exclusive, whether both may be supplied together, or what the response shape/pagination is, which matters for a two-optional-param 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?

Two compact sentences, front-loaded with the resource and its categories, followed by a short licensing note. No filler or repetition; the only mild redundancy is that the category list echoes the kind parameter already spelled out in the schema.

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, no-required-param, no-output-schema lookup tool, the description covers what is returned (bilingual clause text) and the reuse terms. It leaves a real gap around lookup semantics — whether passing id returns a single clause, whether kind returns a list of all clauses in that category, and what happens when both are given.

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% — both id ('条款编号，如 lien-01') and kind ('po / lease / lien / insurance / rwa / audit；不填返回全部') are already documented in the schema, including the default-when-omitted behavior. The description's category list roughly mirrors the kind enum but adds no new meaning such as precedence between id and kind.

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 opening '取合同条款模板' gives a specific verb plus resource, and the parenthetical enumerates the six template categories (采购订单/租赁/抵押担保/保险/RWA 入池/尽调), so an agent can immediately tell this is a static template-retrieval tool. It does not explicitly contrast itself with siblings like cvin_permits or cvin_report, so it stops short of full sibling differentiation.

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

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

Usage is only implied: '可直接粘贴进合同' conveys the purpose context (drafting contract text) but there is no explicit statement of when to call this versus sibling tools, nor any exclusion or prerequisite. The licensing sentence ('永久免费，复制与引用无需署名') is reuse guidance rather than invocation 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 disclose a genuinely important trait: the serial number stays local and only a hash is uploaded for registration, implying a network side effect. It leaves idempotency, determinism, failure modes, and what exactly gets registered/side effects on the server 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?

A single compact sentence with a parenthetical for the privacy constraint and a one-word cost note; purpose is front-loaded and no clause is filler. The 'free' tag is a minor commercial nudge but relevant to tool choice.

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?

Five all-required parameters, no annotations, and no output schema, yet the description never describes the returned CVIN (format, length, whether a registration record is echoed). For a tool whose entire output is a single derived identifier, that is a substantive omission.

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 only 20% (only serial is documented), so the description must compensate; it does by mapping all five Chinese field names onto the required parameters (mfr/model/form/mem/serial). It adds no format or convention guidance, e.g. how to express memory capacity or manufacturer naming, so gaps remain for three of the parameters.

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

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

Description states a specific verb and result ('compute CVIN') and enumerates the five inputs it derives it from (manufacturer/model/form/memory/serial), so the agent knows exactly what the tool produces. It does not name or contrast itself with siblings such as cvin_verify or cvin_resolve, so differentiation is left to inference.

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

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

No explicit when-to-use guidance, no prerequisites, and no named alternative among the 14 cvin_* siblings. The phrase about the hashed result 'participating in registration' hints at a registration workflow, but the agent is not told when to encode versus verify, resolve, or look up identity.

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 behavioural burden: it does disclose that this is a free, foundational event stream usable incrementally, which tells the agent cost and freshness behaviour. It says nothing about ordering, pagination behaviour when limit is hit, or rate/retention characteristics, which matter for a stream-consumption 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?

Three short sentences, front-loaded with what is pulled, followed by the incremental cue and the cost note. No filler, though the trailing "事件流是地基层" is more marketing than actionable 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 read-only stream tool with no output schema, the description conveys what kinds of events arrive and that incremental fetching works, which covers the essentials. It stops short of describing the shape of a returned event or how limit interacts with the stream, leaving an agent to discover that empirically.

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 75%, with since, types and severity_min already documented in the schema; the description mainly reinforces `since` as the incremental cursor and gives example values that map onto `types`. The undocumented `limit` parameter gets no clarification from the description, so it adds little beyond the schema.

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

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

"拉取结构化事件流" gives a specific verb plus resource, and the enumeration (失联、休眠、重复抵押、价格暴跌、跨地区流转) makes the domain of returned events concrete. It does not, however, distinguish this from neighbouring tools such as cvin_risk_signals or cvin_history, so an agent still has to guess which one to reach for.

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?

"支持 since 增量拉取" implies the intended pattern for incremental polling, which is a real usage cue. There is no when-not guidance, no mention of alternatives, and no statement of prerequisites or limits, so usage is only 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?

No annotations are supplied, so the description carries the burden. It does add real behavioral context: the seats are currently all vacant (materially affecting whether governance is operational), the result is free/no cost, and redlines=true triggers a recomputable six-red-line check. It never states the access model or that the call is read-only and side-effect free, nor the output form.

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 dense, front-loaded sentence that leads with the resource and then lists contents, followed by the single conditional behavior. No filler; the trailing '免费' earns its place as a cost disclosure. Slightly list-heavy but appropriate for this kind of reference 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-optional-boolean, no-annotation, no-output-schema tool, the description covers the main risk: it tells the agent what content areas come back and what the flag adds. The remaining gap is return format and whether the governance data is static reference text or computed state, which matters given the 'currently all vacant' note.

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 is already described as 'whether to include red-line self-check results'. The description goes beyond that by specifying there are six red lines and that the determination is recomputable, which tells the agent this flag yields auditable output rather than a summary. That is genuine added meaning over the schema, though it does not explain default behavior when omitted.

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 resource (governance structure) and enumerates its distinct contents: three-tier committee power separation, 7-seat composition, voting thresholds, initiator power-transfer checklist, RFC proposals and public comment period. That is concrete enough to distinguish it from siblings like cvin_clauses or cvin_permits. It loses a point for having no verb (no 'returns'/'retrieves') and for never naming a sibling it is not.

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

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

There is no statement of when to use this tool versus the thirteen sibling tools, no prerequisite or caller guidance. The only conditional hint is implicit in the parameter ('redlines=true 时附带…'), which tells the agent how to shape the output but not when to reach for this tool at all.

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 supplied, so the description carries the full disclosure burden. It does add genuinely useful behavior beyond the schema — that results contain a hash chain and that each call is billed $0.05 via x402 (a real cost/auth prerequisite) — but it omits what happens for an unknown CVIN, whether errors or empty results are returned, and how the limit interacts with a 100-record cap.

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

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

Two short sentences with zero waste: the resource and return content come first, then the billing note. Nothing is padded and the key constraint (per-call cost) is surfaced early.

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 should compensate further for a read-only, paid lookup tool. It covers content (hash chain) and cost, but says nothing about pagination/limit semantics, response shape, or error behavior for an unresolved CVIN.

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%, so both cvin and limit are already documented and the baseline is 3. The description adds only that the history is 'complete', which slightly undercuts the limit parameter rather than clarifying it; no additional semantics for cvin format or limit behavior are 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?

States a specific verb+resource: returns the full observation history for a given CVIN, including the hash chain, and ties it to a concrete purpose (double-collateralization and default-history checks). It does not name or distinguish itself from near siblings like cvin_events or cvin_provenance, so an agent must infer the boundary.

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 用于重复抵押与违约史核查 gives a clear usage context, which is more than a bare purpose statement. However, with 13 sibling tools including cvin_events, cvin_provenance and cvin_risk_signals, no when-not-use case or explicit alternative is offered, leaving selection to inference.

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

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

No annotations are supplied, so the description must carry the full burden, and it goes partway by disclosing the return content: level, what the level can and cannot assert, and how to upgrade. However, it says nothing about whether the query consumes credits aside from 'free', what happens if the CVIN is unknown or malformed, or whether the call has side effects on level state.

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

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

One sentence that front-loads the verb and resource, then packs the level taxonomy and the upgrade path, with a trailing cost note. No filler, and the most decision-relevant information comes first.

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

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

With no output schema and no annotations, this description does the essential work: it defines the level taxonomy and names the three things returned. What is missing is input-side detail (CVIN format, invalid-ID behavior) and sibling routing, but for a single-parameter read tool the specification is close to 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 description coverage is 0% for the single required 'cvin' parameter, so the description must compensate and does not: it never states the CVIN format, where to obtain one (plausibly cvin_encode or cvin_resolve), or whether case/prefix matter. The description adds meaning only about the tool's output, not its input.

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 (查询, query) and resource (某 CVIN 的身份级别) and even enumerates the three-level model (L0/L1/L2) it reports on, so the agent knows exactly what it gets back. It does not differentiate itself from plausible overlaps such as cvin_verify or cvin_resolve, which prevents a 5.

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

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

Usage is only implied by the purpose: look up a CVIN's level and its upgrade path. There is no explicit when-to-use versus alternatives (e.g. cvin_verify for verification, cvin_resolve for resolution) and no when-not-to-use guidance. The '免费' (free) note is a mild decision aid, not 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?

No annotations exist, so the description carries the burden and does well: it discloses the free/cost profile, that results are per-platform latest quotes with inventory and observation timestamps, and that the data is supply quotes not tied to a specific device. It stops short of describing result cardinality, pagination, or quote freshness guarantees, which keeps it from 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 query purpose and return fields, then the input format, then the cost note, then the scope/alternative routing. Every clause carries information; nothing is redundant padding.

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

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

For a one-parameter read tool with no output schema and no annotations, the description supplies return fields, input flexibility, cost, and scope limits. Only minor operational details (how many platforms, pagination, freshness window) are left unstated.

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, but the description adds genuine meaning: a bare model like 'h100' or 'rtx4090' is auto-resolved against the vendor prefix, clarifying runtime matching behavior beyond the schema's enumeration of accepted forms.

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 ('查询某 GPU 型号的租赁行情') and enumerates what is returned (price/region/inventory/observation time). It also explicitly marks the scope boundary versus cvin_resolve and cvin_history, so an agent can tell it apart from siblings 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?

Gives an explicit when-to-use condition (model-level supply quotes) and a when-not case with named alternatives: verifying a specific device should go to cvin_resolve or cvin_history. It even notes the call is free, removing cost-related hesitation.

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 well: it declares the return shape {allowed, level, upgrade_to}, states the tool is free (no cost/rate concern), and characterizes the operation as a deterministic check. It does not state error behavior for unrecognized 'use' values or whether the check is logged/audited, which keeps it from 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?

Three short sentences: what it decides, what it returns, and why it exists. Nothing is redundant and the key 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 two-parameter predicate with no output schema and no annotations, the description supplies the decision semantics, the return contract, and the cost profile – enough to call it correctly. The remaining hole is the undocumented 'cvin' input and behavior on unknown use values.

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 50% – 'use' is well documented in the schema with the same examples the description repeats, while 'cvin' has no schema description at all. The description only indirectly compensates by framing cvin as an '身份级别', so the format/encoding of that identifier remains unexplained.

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?

It names a specific verb (judge/check) and resource (whether an identity level permits a given use), with concrete use examples ('抵押登记'/'保险核保'/'资产池入池') that make the intent unmistakable. It does not explicitly distinguish itself from near neighbors such as cvin_identity or cvin_verify, so sibling differentiation is only implicit.

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

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

Usage is implied: call it as a gate before an action that requires a level ('由机器把关'), and the returned upgrade_to hints at a remediation path. There is no explicit when-not guidance and no named alternative for related lookups (e.g. fetching a raw level via cvin_identity), so the agent must infer 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 supplied, the description carries the whole disclosure burden. It does add real behavioural substance — the two segmentation levels (device vs. model), the source breakdown, the fixed 10% threshold comparison, and the fact that no parameters or cost are involved — but it never states that the call is side-effect free or describes the shape of the returned figures.

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 front-loaded with the resource and then lists the four computed metrics compactly, with the usage trigger and cost note at the end. It is dense but every clause adds information; the only mild cost is the list-like density of the first sentence.

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

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

For a zero-parameter tool with no output schema and no annotations, the description does the heavy lifting by enumerating what comes back: real/synthetic counts at two granularities, source list, and threshold shortfall. It is nearly complete for the call decision; only the concrete return format and whether figures are cached or live are absent.

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 is an empty object, so there are no parameters whose meaning could be lost; the zero-parameter baseline applies. The description implicitly confirms this by describing a self-contained, parameterless statistic call.

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 resource (data provenance / synthetic-data ratio) and enumerates exactly what it reports: real vs. synthetic counts, computed separately at device level and model level, the contributing sources, and the gap to the '≤10% synthetic' threshold. This is far more specific than the name alone, though it does not name or contrast any sibling tool, so an agent must infer the boundary against tools like cvin_verify or cvin_risk_signals.

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 when-to-use trigger — check this before citing registry-table statistics — plus a cost signal ('免费') that helps prioritise the call. It stops short of exclusions or naming an alternative tool for cases where provenance is not needed, so it is context-rich 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 behavioral burden and discloses important traits: the report includes a report number, ed25519 signature, and fixed content hash; it is archival and independently verifiable; and it costs $2.00 per copy via x402. It does not cover payment failure behavior, permissions, or return delivery details, but it is materially more informative than the schema alone.

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

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

The description is a single compact sentence with the main action front-loaded, followed by parenthetical report contents and billing details. Every component adds useful information with no redundant wording.

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 explains the report contents, intended archival use, and pricing. It is nearly complete, though the lack of cvin semantics and exact response structure leaves minor 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?

The only parameter, cvin, has 0% schema description coverage, so the description should explain its meaning and format. It only implies that cvin refers to a single device and does not define the identifier format, validation rules, or examples.

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 a specific verb and resource: issuing a formal verification report for a single device. It includes distinguishing details such as the report number, ed25519 signature, content hash, and archival use, though it does not explicitly contrast this with sibling tools like cvin_verify.

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

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

It gives a clear when-to-use context: for archiving loan, underwriting, and lease decisions. It does not provide explicit exclusions or name alternatives such as cvin_verify, so the guidance is clear but incomplete.

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 the cost and rate-limit profile ('永久免费、无限次') and the read-only registry-lookup nature plus the returned fields. The main gap is that it never states what happens when the CVIN is absent from the registry (a null result, an error, or a not-found status), which matters most for a lookup 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?

It is two sentences with zero waste: the action and its scope come first, followed by the returned fields and the cost/limit note. Every clause carries information an agent can use before calling this 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?

This is a simple one-parameter lookup with no output schema and no annotations, so the description must carry the return shape — and it does by naming the returned observation fields and price observation. The only real missing piece for a tool of this complexity is not-found behavior and whether calls are idempotent/cached.

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, and schema coverage is 100% — the schema already supplies the canonical format 'cvin:nv.h100.sxm.80g:6a1kfvdo43buqm34'. The description adds no meaning beyond that baseline, and it does not say whether a malformed CVIN is rejected or normalized, so the 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 states a specific verb (解析/确认) and resource (一个 CVIN) and then enumerates the returned facts (首次/最近观测时间、观测次数、观测类型、最近一次价格观测), so an agent knows exactly what the call produces. It never contrasts itself with the overlapping sibling cvin_verify, which also sounds like a verification-style lookup, so sibling differentiation is missing.

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

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

Usage is only implied: the text says the call is '永久免费、无限次', which removes cost as a decision factor, but it never says when to resolve a CVIN versus cvin_verify, cvin_identity, or cvin_history, nor does it name any prerequisite workflow. There are no explicit exclusions or alternatives, so the agent must infer the fit from the sibling names.

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 exist, so the description carries the full burden. It does disclose one genuinely useful behavioral trait — below 200 events only counts are returned, no ratios — plus that the tool is free. However, it says nothing about read-only nature, latency, caching, or the shape of what comes back, which leaves meaningful gaps for a no-annotation 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?

Very compact and front-loaded: the metric list comes first, then the threshold rule, then the cost note. The parenthetical '（先计数后比率）' restates the preceding clause and is mild redundancy, keeping it from a 5.

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?

There is no output schema and no annotations, so the description must convey what comes back — it does so by enumerating the output categories (distributions and counts) and defining the threshold gating rule. An agent can call it correctly with no inputs. What is missing is any hint of the response structure or scoping (e.g. global vs per-entity), which a rich-output tool would benefit from.

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

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

The tool takes zero parameters and the schema is an empty object, so there is no parameter meaning to add. Baseline 4 applies; the description correctly implies the tool is parameterless by describing a fixed aggregation scope.

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 (聚合/aggregate) and resource (风险信号/risk signals) and enumerates the constituent metrics: identity-level distribution, activity distribution, in-custody and duplicate-collateral counts, event counts. This lets an agent tell it apart from raw-list siblings like cvin_events or cvin_identity. It stops short of naming an alternative tool explicitly.

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

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

Usage is only implied: an agent can infer this is the aggregate/overview entry point rather than a per-record lookup, but there is no explicit 'use this when…' statement, no prerequisites, and no named alternative among the 13 siblings. The 200-event threshold note is a behavioral rule, not selection 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 exist, so the description carries the full burden. It usefully discloses the evaluation criteria per device and the shape of the deliverable, plus that the call is free. It does not state that the operation is read-only with no side effects, whether any record is written or cached, or what happens to the entries that fail, which are the details an agent needs before batch-running 500 CVINs.

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?

This is one dense sentence that leads with the purpose, follows with the per-device decision list, and then states the output form. The trailing '免费' is small but useful and does not distract. It is efficient, though the parenthetical enumeration makes the sentence long.

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 four parameters, no annotations, and no output schema, the description does reasonable work: it explains what is evaluated and what the return artifact is (a contract-annex-ready list). It leaves open how failures are reported, whether results are paginated at the 500 limit, and how it relates to sibling verification tools, so it is complete enough but not exhaustive.

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%, with devices, purpose, reference, and counterparty each documented in the schema itself, so the baseline of 3 applies. The description adds no meaning beyond that, though it does convey that the tool operates on a batch of devices, which is consistent with the array 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 states a specific verb and resource: it generates a pledge collateral schedule (抵押物清单生成) for a set of CVINs. It even enumerates the four per-device decisions it makes (identity level adequacy, existing pledge, duplicate pledge, synthetic history). It never names or differentiates itself from close siblings like cvin_report or cvin_verify, so sibling disambiguation is missing.

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

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

Usage is implied by 'given a set of CVINs' and by the stated outcome of producing a list usable as a pledge-contract annex, which tells the agent the context in which this tool fits. There are no explicit when-not conditions and no named alternatives, so the agent must infer the boundary with cvin_verify, cvin_identity, and cvin_report.

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 load, and it does disclose real operational facts: the tool replays a hash chain (a read-style operation), returns an ed25519 signature, and costs $0.05 per call via x402, which implies a payment prerequisite the agent must handle. It says nothing about error behavior for broken or invalid chains, rate limits, or the response shape beyond the signature itself.

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

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

Two short sentences with the purpose front-loaded and the billing note appended; nearly every clause earns its place. The only mild slack is the marketing-adjacent phrase about anyone being able to independently recompute the signature, which does double duty as a verification guarantee.

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, cost and payment mechanism, and the nature of the output, which is reasonable. It still leaves an agent without the CVIN format, the failure semantics for an invalid chain, and any differentiation from the many sibling cvin_* tools.

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

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

The single parameter cvin has 0% schema description coverage, so the description must compensate, and it only refers to "该 CVIN" (this CVIN) without explaining what a CVIN is, its format, or its expected syntax. An agent knows it must pass an identifier but not what a valid value looks like.

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: it replays this CVIN's hash chain (重放该 CVIN 的哈希链) and returns an ed25519 signature. That is far more specific than the tautological name cvin_verify, though it never explicitly distinguishes the tool from siblings such as cvin_history or cvin_provenance.

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 no explicit when-to-use guidance and names no alternative tool, so an agent must infer when to verify a chain rather than call cvin_history or cvin_provenance. The note that anyone can independently recompute the signature hints at an audit or third-party verification use case, but it never states that use case as a condition.

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