Vulnify MCP

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

Annotations already establish readOnly/idempotent/non-destructive, and the description goes well beyond them: it discloses that this skips the PII scan, records no security event and no audit entry, performs no DLP scan, has no content field, and returns no event id or finalDecision, plus a concrete rate limit of 60 requests/minute/key. That is exactly the side-effect and constraint 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?

Every sentence is front-loaded with actionable information and none is filler: usage condition, endpoint, side-effect profile, sibling routing, rate limit. Dense but each clause earns its place.

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

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

For a dry-run tool with an output schema present, the description covers everything the agent needs: trigger condition, scope of the check, side effects, rate limit, and sibling alternatives. Return-value shape is intentionally signaled ('no event id and no finalDecision') rather than fully specified, which is appropriate given the output 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%, so all six parameters (including both enums) are already fully documented in the schema, which sets the baseline at 3. The description adds only marginal parameter meaning by noting the absence of a content field and clarifying that no DLP scan occurs, which largely restates the schema's own note on containsSensitiveData.

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+resource ('Dry-run a proposed action against the organization policies') with the exact endpoint, and explicitly differentiates itself from siblings decide_action (records a decision) and test_policies (batch up to 200 cases). 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?

It opens with the triggering condition ('Use for what-if questions when you are not about to act') and names the alternative that does record ('decide_action is the call that records a decision'), plus routes batch needs to test_policies. When-to-use, when-not-to-use, and alternatives are all present.

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

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

Annotations only carry the readOnly/destructive/idempotent/openWorld hints, and the description adds substantial context beyond them: it writes a security event and an audit entry, the tool arguments are never executed, finalDecision is the authoritative output, REVIEW/BLOCK means the downstream tool was denied, the review cannot be approved here, and idempotencyKey governs retry behavior. This is exactly the side-effect and outcome disclosure a security-gate tool 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?

Front-loaded with the core action and delivered in short, information-dense sentences with no filler. It reads as a flat list of facts rather than organized prose, but each sentence carries distinct, 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?

An output schema exists, so return values need not be enumerated, and the description still flags the critical output field (finalDecision is authoritative) plus the meaning of REVIEW/BLOCK. For a write-bearing security gate with 11 parameters it covers the important behaviors, though it could be clearer about how a caller should act on an ALLOW versus a REVIEW outcome.

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 schema already documents all 11 parameters (substring mapping, agent/agentId alternatives, content not stored, idempotencyKey 24h window, etc.). The description largely restates that material ('The tool arguments are not executed', the idempotencyKey behavior) rather than adding new parameter meaning, 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?

States a specific verb and resource ('Records a decision for a downstream MCP tool call') and pins it to an endpoint, so the agent knows exactly what operation it is. It names the sibling decide_action and explains the relationship ('returns the same recorded decision as decide_action'), which helps differentiate, though it never states plainly why one would pick this over decide_action.

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 stated: the tool is scoped to downstream MCP tool calls that Vulnify maps by substring, which hints at the MCP-specific case versus the generic check_action/decide_action. There is one useful when-not signal ('This server cannot approve the review'), but no explicit 'use this instead of X when Y' 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 annotations only covering broad hints, the description carries the load and does so richly: it writes a security event and audit entry, consumes organization quota, may trigger human review, does not itself approve reviews, and content is scanned in memory and not stored. The idempotencyKey explanation (same key returns stored decision for 24h) refines rather than contradicts idempotentHint=false, which describes default behavior.

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

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

Front-loaded with the trigger condition and the outcome-to-action mapping, which is the highest-value content. It is dense and somewhat long, but nearly every sentence (finalDecision vs decision, REVIEW persistence, idempotency) adds decision-relevant information rather than 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 consequential gating tool with an output schema present, the description still explains the return semantics (finalDecision is authoritative; decision does not change on resolution; REVIEW/BLOCK mean the action was not allowed). Combined with full schema coverage, nothing an agent needs to call it correctly 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%, so the schema already documents all 9 parameters, including the enum values and idempotencyKey behavior. The description's mentions of content scanning and idempotency largely restate schema text, so this is correctly a 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?

Opens with a specific trigger ('Call this before a consequential action with any tool or connector') and states the resource is a recorded decision for a proposed action (POST /v1/events). An agent can distinguish it from siblings like get_decision and check_action 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 enumerates when to call it (sending email/messages, exporting/sharing data, deleting, production/financial writes, payments, external API writes) and prescribes per-outcome behavior for ALLOW, REVIEW, and BLOCK, including the follow-up call to get_decision. Nothing is left to inference.

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

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

Annotations already cover the safe-read profile (readOnly, idempotent, non-destructive), and the description adds genuine behavioral context: the state transition from REVIEW to ALLOW/BLOCK, that decision is immutable while finalDecision is authoritative, and the 30-second bounded wait. It omits error/not-found behavior, but the added semantics are substantial.

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 verb, resource, and endpoint, then spends its remaining sentences on the semantics an agent actually needs (state transitions, polling bound, timeout flag). No filler or restated name/title.

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 annotations carrying the safety profile, a 100%-covered schema, and an output schema, the description only needs to supply the non-obvious semantics, and it does: finalDecision authority, polling termination conditions, and the non-mutating boundary.

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 id, waitMs, and pollIntervalMs are already fully documented with constraints. The description paraphrases waitMs polling behavior but adds no syntax or format detail beyond the schema, 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?

States a specific verb and resource ('Read a recorded decision (GET /v1/events/{id})') and clarifies the scope includes a REVIEW, with the explicit boundary 'This does not approve or deny the review' separating it from decide_action.

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?

Explains clearly when to supply waitMs (while finalDecision is REVIEW, to poll until ALLOW/BLOCK or timeout) and what waitTimedOut means, plus when not to use it. It never names decide_action as the alternative for resolving a review, so the routing guidance is one step short of 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?

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), yet the description adds genuinely new context: a 60 requests/minute/key rate limit, the auth requirement (any non-revoked API key), and the sort order of results. It does not describe error or pagination behavior, so it falls 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?

Three short sentences, front-loaded with purpose and endpoint, then behavior and constraints. Every sentence carries distinct information (endpoint, return shape, auth, rate limit) with no 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 parameterless read tool with an output schema and full annotation coverage, the definition supplies everything an agent needs: endpoint, authenticated-access rule, rate limit, and result ordering. Nothing material 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 tool takes zero parameters, so there is nothing for the description to disambiguate; the schema is empty and fully covered. Baseline 4 applies for a no-parameter tool.

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

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

States a specific verb and resource ('List the organization policies as code') and pins the underlying endpoint (GET /v1/policies), which clearly separates it from mutating siblings like plan_policy_changes. It stops short of naming an alternative sibling or stating when this read is preferred over test_policies.

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

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

Usage is implied by the read-only list semantics and the note that any non-revoked API key may call it, which tells the agent it needs no special scope. There is no explicit when-to-use/when-not-to-use statement or routing to a sibling such as test_policies or plan_policy_changes.

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?

Goes well beyond the annotations: dryRun is forced true and non-negotiable, nothing is stored, no audit entry is written, prune only marks deletions in the plan, and an org-wide LIVE key is required (TEST or agent-bound keys get a 403). This is exactly the operational context an agent needs before calling a policy 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?

Six short sentences, all front-loaded with the highest-value fact first (no writes) and none wasted. The endpoint, side-effect, parameter note, and auth constraint each earn their 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?

For a read-only preview tool with an output schema present, the description covers everything left unspecified: safety profile, side effects, parameter caveats, and authentication requirements. An agent has no unanswered question that would cause a wrong 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 coverage is 100%, so the baseline is 3, but the description adds real value by clarifying prune's narrow effect and by stating that dryRun is forced and not a user-controllable input. It does not, however, add anything about the nested policy object beyond what the schema already documents.

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 (diff) and precise resource (policy creates, updates, and deletes), and even names the underlying endpoint POST /v1/policies/apply. The phrase 'without writing them' instantly separates it from a mutation tool and from siblings like test_policies or list_policies.

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?

Clearly frames the tool as a preview step ('This tool does not apply the plan'), which tells the agent when it is appropriate. It does not name the sibling that performs the actual apply, so the routing is implied rather than explicit; the auth conditions also function as usage preconditions.

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

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

Annotations already declare readOnly/idempotent/non-destructive, yet the description adds substantive behavior: nothing is written when 'policies' is set, the PII scan is skipped, 'pass' is null when 'expect' is omitted, and a concrete rate limit of 60 requests/minute/key. These are exactly the traits an agent cannot infer from structured fields.

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?

Short sentences with the purpose and endpoint front-loaded and the rate limit sensibly at the end. Mild redundancy: 'up to 200 policy cases' in sentence one is repeated as 'One call covers up to 200 cases' later, and that limit is also in the schema (maxItems 200).

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 rich annotations and an output schema present, the description still covers the pieces an agent needs: two operating modes, the no-write guarantee, the skipped scan, nullable results, and throughput/rate limits. Nothing required to call it correctly 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 coverage is 100%, so the baseline is 3. The description restates the omitted-vs-set semantics of 'policies' that the schema already documents, adding little new meaning beyond what the structured field 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+resource ('Evaluate ... policy cases') plus the endpoint and scope ('up to 200'), and the dry-run character ('without recording an event') sets it apart behaviorally from write-oriented siblings. It never names an alternative (check_action, decide_action) to anchor the distinction, 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?

Gives clear conditional context: omitting 'policies' uses stored policies, setting it evaluates proposed ones. It also discloses a usable limitation ('skips the PII scan: cases have no content field'). No explicit when-not or sibling routing, so 4 rather than 5.

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