MarketNow MCP

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 disclose the key outcome: returning a risk score and reasons. It does not state whether the operation is read-only, whether external lookups occur, or any side effects, though 'check' implies a non-mutating lookup.

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 convey purpose, scope, and output with no filler. The key phrase 'Check if a domain is suspicious' is front-loaded and immediately clear.

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

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

For a one-parameter tool with no output schema, the description covers the core action and return value adequately. It lacks usage guidance relative to verify_trust and does not describe the return structure, but the low complexity makes these gaps minor.

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 schema already defines the single required domain parameter with an example. The description adds no further semantic detail about input format, normalization, or edge cases 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?

The description clearly states the tool checks whether a domain is suspicious and returns a risk score, with 'scam checker' adding useful context. It does not explicitly differentiate it from the sibling marketnow_verify_trust, which could overlap in trust-related checks.

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 about when to use this tool versus alternatives such as marketnow_verify_trust. The only implied usage is checking domain suspicion, leaving the agent to infer selection criteria.

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 behavioral burden. It discloses fail-closed behavior (UNKNOWN+DENY), the full set of response statuses with PERMIT/DENY recommendation, and the independent verifiability via Ed25519. This goes well beyond a simple purpose 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?

Three sentences with zero fluff: purpose is front-loaded, then return semantics and fail-closed behavior, then verification detail. 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?

Covers return values, fail-closed policy, and verification. Missing guidance on parameter combinations (e.g., both card_id and kid provided, or neither) and any authentication requirements, but for a read-only check with all-optional parameters it is largely 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 100%, so the baseline is 3. The description additionally clarifies the role of card_id and kid (the two lookup paths) and implies nonce is for anti-replay, adding meaning beyond the schema definitions.

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: 'Check the revocation status' of an Agent Trust Card (card_id) or CA key (kid), and lists the exact statuses returned. This clearly differentiates it from siblings like marketnow_check_domain and marketnow_verify_trust, even without explicitly naming them.

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

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

Usage is implied ('Check revocation status') but there is no explicit guidance on when to use this tool versus alternatives such as marketnow_check_domain or marketnow_verify_trust. No exclusions or 'when not to use' statements are given, leaving the agent to infer applicability.

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 of behavioral disclosure. It does well by stating the exact computation (RFC 8785 JCS + sha256 per tool, plus a manifest fingerprint) and the drift-report output when pinned is supplied. It does not go into error behavior or formatting details, but the core behavior is 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?

Two dense sentences carry purpose, method, optional workflow, and security motivation without redundancy. The most important action is front-loaded, and the parenthetical OWASP reference adds credibility without bloating the text.

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

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

For a moderately specialized tool with no output schema, the description covers what the tool does, how it hashes, and what the pinned parameter enables. It stops short of describing the exact manifest/report shape, but the drift-report semantics (added/removed/changed) are explicit enough for an agent to use it 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 description coverage is 100%, so both parameters are already documented in the schema. The description adds a useful clarification that pinned is a previous manifest for drift detection, but it does not materially expand beyond the schema's own descriptions.

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: it cryptographically fingerprints MCP tool definitions, and it ties that to a concrete security goal ('verify tool descriptions haven't changed'). It also distinguishes itself from the sibling tools, which are all domain/verification utilities rather than fingerprinting operations.

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

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

The description clearly states when to use the tool: to detect changes in tool definitions and to guard against tool poisoning or rug-pull redefinitions. It also explains the optional pinned-manifest workflow for drift detection, though it does not explicitly discuss when not to use it or name alternatives.

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. 'Get' implies a read-only operation, but the description does not explicitly confirm no side effects, permissions, or what 'details' will contain. It is not misleading, but it is thin.

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

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

The description is a single, front-loaded sentence with no filler. Every word adds relevant information about what the tool returns.

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 zero-parameter getter, the description names the resource and is likely callable without confusion. However, there is no output schema and 'details' is vague, so the description does not fully specify what the agent should expect in the 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 tool has zero parameters and schema coverage is effectively 100%, so there is nothing the description needs to add about parameter meaning. The baseline of 4 applies here.

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 ('Get') and a distinct resource ('12-stage verification pipeline details'), so an agent can tell it is a retrieval for the pipeline rather than the sibling tools. It does not explicitly contrast with siblings, which keeps it from 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 guidance about when to call this tool versus marketnow_check_domain, marketnow_verify_trust, or the other siblings. For a zero-parameter getter the usage may seem obvious, but the description provides no context or exclusions.

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 burden. The verb 'list' implies a read-only operation, but the description does not explicitly state that it has no side effects, does not require authentication, or any other behavioral details. For a simple read operation, this is minimally sufficient, but it doesn't disclose any additional constraints or return format.

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 concise sentence that front-loads the action. It has no fluff and communicates the essential information 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?

For a tool with no parameters and no output schema, the description is complete. It specifies the exact scope ('all 8') and what is included ('algorithms and status'). No additional information is needed for an agent to invoke it 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?

There are zero parameters, so the schema already covers everything. The description doesn't need to add parameter details. Baseline for 0 params is 4, and there is no reason to lower 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 states a specific verb (list), a specific resource (all 8 supported credential formats), and the content (algorithms and status). It clearly distinguishes from siblings like marketnow_check_domain or marketnow_translate_credential, which are different operations.

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

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

The description does not provide any when-to-use guidance or mention alternatives. It simply states what it does. There is no indication of when to choose this tool over the sibling tools, though the purpose is clear. For a simple listing tool, this might be acceptable, but explicit guidance is absent.

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 behavioral burden. It adds useful context about the indexed sources and security scoring, but it does not disclose result format, ranking behavior, authentication needs, rate limits, or limitations of the search index.

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

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

A single sentence front-loads the action and resource with no filler. Every phrase adds context about scope or scoring.

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

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

For a simple two-parameter read-only search with no required fields and no output schema, the description conveys the core scope sufficiently for basic invocation. Minor gaps remain around return expectations and search behavior, but they are not critical for this tool's complexity.

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 the baseline is 3. The description adds no parameter-specific meaning beyond the schema's 'Search query' and 'Filter by category'.

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: 'Search the MarketNow registry of indexed MCP servers,' and adds useful scope detail ('68k+ across GitHub, npm and PyPI, security-first scored'). This clearly distinguishes it from sibling tools like marketnow_verify_trust or marketnow_submit_skill.

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 rather than explicit: an agent can infer this is for finding MCP servers in the registry. However, there is no explicit when-to-use guidance, no mention of when not to use it, and no direction toward alternatives among the 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 full burden of behavioral disclosure. It details the validation pipeline (Sentinel-scan, live URL/package checks), rejection with 422, acceptance flow (certified-L1.5, pending L2 review), description-only never merged, pricing flexibility, no auth, and secret rejection. This is exemplary transparency beyond what the schema could convey.

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 paragraph that opens with the core purpose and then packs in validation details, rejection behavior, acceptance flow, pricing policy, authentication, and a security warning. Every sentence carries essential information; there is no filler, and it is efficiently 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 complex submission tool with no output schema, the description covers validation, rejection, storage in the auditable queue, review status, description-only handling, pricing, authentication, and secret handling. It gives an agent a complete picture of what will happen when the tool is invoked. The absence of an explicit return-value description is not a gap given the depth of behavioral 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 schema covers 100% of parameter descriptions, so the baseline is 3. The description adds meaningful semantics by explaining that repo_url is probed for HTTP 200 and install must reference a real package on npm/PyPI/crates/Docker Hub, and clarifies that pricing is vendor-set and security-verified rather than regulated. These details extend beyond the schema's property descriptions.

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 'Publish a skill to the MarketNow catalog (the write side)', which is a specific verb and resource, and explicitly marks it as the write counterpart to the other read/verification sibling tools. This makes the tool's role unmistakable even without opening the 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 description provides clear context by calling it 'the write side', implying it is for submission while siblings like marketnow_check_domain, marketnow_verify_trust, and marketnow_search_skills handle other concerns. It does not explicitly name alternatives or state when not to use it, but the context is strong enough to guide selection.

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 'Lossless conversion through Universal Trust Schema' does add a meaningful fidelity guarantee and a hint about the conversion pipeline. It still omits operational details such as whether the source payload is left unchanged, what happens with unsupported source/target pairs, and what the result shape is, especially since there is 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 definition is two short sentences with the verb and object up front; there is no filler or restatement of the tool name. The format list is compact and the Universal Trust Schema clause adds value without bloating the text.

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

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

For a simple three-parameter transformation tool, the description is enough to make a basic call: pick a from format, a to format, and a payload. However, the absent output schema, lack of error/edge-case behavior, and format-list mismatch leave meaningful gaps for an agent trying to invoke it robustly.

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 already covers all three parameters, so the baseline is 3, but the description's eight-format list conflicts with the six formats in from/to. This can lead an agent to pass values like 'EAT-AI' or 'ZTA' that are absent from the schema descriptions, making the prose actively misleading rather than merely redundant.

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 operation—translating a credential between formats—and distinguishes it from the sibling domain/pipeline/verification tools. However, it claims 8 formats while the schema's from/to descriptions list only six values, so the agent gets an inconsistent picture of what the tool accepts.

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 verb 'Translate' implies the obvious use case, and none of the sibling tools appear to perform translation, so an agent can infer when to call it. That said, the description gives no explicit conditions, prerequisites, or exclusions such as 'use verify_trust when you only need validation.'

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 behavioral disclosure. It states the verification pipeline and return categories, but leaves unaddressed whether the operation is read-only, contacts an external UTA service, stores the credential, or has failure modes. This is adequate but has clear gaps.

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 filler: the first names the action and scope, the second names the outputs. Key format information is front-loaded before the return value list.

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-required-parameter tool, the description covers input type, supported formats, pipeline, and output categories despite having no output schema. It would be more complete with error behavior or response structure, but nothing essential for selecting and invoking it 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?

The schema already defines credential as a JSON string or JWT at 100% coverage. The description adds value by listing the concrete supported credential types (W3C VC, MCP Card, ATC v3, A2A, EAT-AI, ZTA, X.509), which helps agents prepare valid inputs.

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 names a precise operation ('verify'), a specific resource class ('AI agent credential'), and enumerates accepted formats, then states the outputs. This clearly differentiates it from siblings like marketnow_translate_credential and marketnow_check_domain.

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 'Verify any AI agent credential' gives clear context for when to call. It does not explicitly name alternatives or exclusions, so it stops short of a 5, but the verify-versus-translate contrast with siblings makes the intended use unambiguous.

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