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

With no annotations, the description carries the full disclosure burden. It does add real behavioral content beyond the title by naming the exact weakness categories (BOLA/IDOR, unauthenticated mutations, missing rate limits, mass assignment), but it never says whether the analysis is static-only, whether code is executed, whether any permission or network access is required, or how findings are reported.

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

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

A single front-loaded sentence with no filler; the verb and resource come first and the detection list follows. The four-item enumeration is information-dense and each item earns its place, though the sentence is long enough to be slightly list-heavy.

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 audit tool with no output schema and no annotations, the description establishes scope but is thin on everything else: no result format, severity model, scope limits, or handling of non-JS frameworks beyond the 'etc.' hint. Adequate to select the tool, incomplete for predicting its behavior.

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

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

Schema description coverage is 100% for both parameters (routeCode, sourceFile), so the schema fully documents them. The description adds no parameter-level meaning such as accepted languages, size limits, or how sourceFile affects reporting, 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 (audits) and a precise resource (REST/GraphQL endpoint handlers), then enumerates the four vulnerability classes it detects. An agent can distinguish this from vulnforge_audit_web and vulnforge_audit_db by the 'API endpoint handlers' scope, though it never explicitly names or contrasts those siblings.

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 agent can infer 'use this when you have API route handler source', but there is no guidance on when to prefer vulnforge_full_scan or the sibling audits, and no prerequisites or ordering advice.

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

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

No annotations are provided, so the description carries the full burden. It usefully names what it detects (injection vulnerabilities, raw interpolations, credential leaks), which is real behavioral value, but it never states that this is a static, non-executing analysis, nor how findings are reported or prioritized.

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

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

A single front-loaded sentence with no filler; the verb, scope, and detection targets are all packed in without 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?

With no annotations and no output schema, the description should say more about what an agent gets back (finding format, severity, whether it only analyzes rather than connects to a DB). It covers the input scope well but leaves the result side underspecified.

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% with only two parameters, so the schema already documents queryCode and sourceFile fully. The description adds no syntax or format detail beyond it, and its mention of 'connection strings' is only loosely reflected in the queryCode schema description, which lists SQL/ORM snippets but not connection strings.

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 gives a specific verb (audits) and enumerates the exact resources in scope: SQL/NoSQL query snippets, ORM commands, and connection strings. That DB-specific framing implicitly separates it from vulnforge_audit_web and vulnforge_audit_api, though it never names those siblings 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?

There is no guidance on when to reach for this tool versus vulnforge_full_scan, nor any mention of the natural audit-then-inject_patch workflow. The usage context (you have a query snippet to check) is only inferable from the resource list.

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

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

With no annotations, the description carries the full behavioral burden, and it omits key traits: whether it is read-only, whether it performs network requests against `url`, authentication requirements, and what all-optional parameters mean (it is unclear what happens when all four are empty). It also never describes the shape or severity of findings, leaving the agent without behavioral context for an audit operation.

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

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

A single dense sentence that front-loads the verb and the audited surfaces, with no filler or repetition. The trailing list of checks is long but each item is substantive, so no sentence needs removing.

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, so the description is the only source for what the tool returns, and it stops at enumerating detection categories without describing result format or severity. It compensates somewhat by implicitly naming the findings an agent should expect, and the input side is fully covered by a 100%-documented 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 description coverage is 100%, so both the parameters and their nested/array types are already documented, which sets the baseline at 3. The description contextualizes what the inputs are used for (headers, cookie strings, HTML/JS sinks) but adds no syntax, format, or combination semantics 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?

States a specific verb ('Audits') plus the exact surfaces inspected — HTTP response headers, cookie flags, and DOM client code — and enumerates the misconfiguration classes it looks for (XSS sinks, weak CSP, missing HSTS, tabnabbing). This target-surface list clearly differentiates it from siblings like vulnforge_audit_api and vulnforge_audit_db, which target different layers.

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

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

There is no when-to-use guidance, no mention of alternatives such as vulnforge_full_scan, and no stated prerequisites (e.g., whether the tool fetches the URL itself or only analyzes supplied artifacts). Usage is only inferable from the tool name and the audited surfaces.

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

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

With no annotations, the description carries the full behavioral burden, yet it omits whether authentication/target access is required, how long a full scan takes, whether generated patches are actually applied or only returned, and what happens if a layer code is omitted (0 required params). It does disclose that output includes unified findings and patches, which is the only behavioral signal.

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

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

A single front-loaded sentence with no filler; the scope and output are stated up front. It could not be much shorter without losing content, though it does no routing work.

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 four-parameter tool with a nested object, zero schema descriptions, no annotations, and no output schema, the description is too thin. It leaves the agent guessing about parameter formats, preconditions, and whether the tool is safe/non-destructive.

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

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

Schema coverage is 0% and the description explains none of the four parameters. The layer names (Web/API/DB) loosely map to frontendCode/apiCode/dbCode, but what those codes actually are (repo paths? endpoints?) and the purpose of 'headers' (auth? request injection?) remain undefined.

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?

Clear verb+resource: 'Runs an end-to-end multi-layer vulnerability audit across Web, API, and DB layers.' The multi-layer scope implicitly distinguishes it from the per-layer siblings (vulnforge_audit_web/api/db), but it never names them or explicitly frames itself as the aggregate alternative.

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

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

No when-to-use guidance is given: it doesn't say when to run the full scan versus the three per-layer audit siblings, nor where vulnforge_inject_patch fits relative to the 'ready-to-apply patches' this tool produces. Only the phrase 'end-to-end' hints at context.

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

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

No annotations are provided, so the description carries the full burden. It conveys that the tool mutates code automatically and lists the transformation classes, but it never says whether the target file is overwritten on disk, whether changes are reversible, what permissions are needed, or whether patched source is returned instead of written. For an unannotated mutation tool this is a substantial gap.

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

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

A single front-loaded sentence that leads with the core action and then lists the specific remediation techniques. It is efficient and wastes no words, though the trailing list of transformation types edges toward detail that could live in an output description.

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 explain what the call yields – patched source text, a file write, or a status report – and it does not. Combined with silence on side effects on the 'filename' target, the definition leaves the agent unable to predict the result of invoking it.

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

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

Schema description coverage is 100% – both 'filename' (with an example) and 'sourceCode' are documented in the schema itself. The description adds no parameter-level syntax, format, or constraint detail beyond what the schema already provides, so the baseline of 3 applies.

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

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

States a specific verb ('synthesizes and automatically injects') and resource ('defensive patches into vulnerable code'), and enumerates the concrete transformations performed (parameterized statements, headers, DOM sanitization). This clearly separates it from the sibling audit_* and full_scan tools, which are read-only detectors rather than remediation.

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 remediation step taken after an audit surfaces vulnerable code, since it takes sourceCode and returns patched output. There is no explicit when-to-use statement, no prerequisite (e.g. 'run vulnforge_audit_* first'), and no guidance on when to choose this over the scan siblings.

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